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Cancer utilization of large glutamine equivalents contributes to diverging glucose-6-P flux toward the pentose phosphate shunt (PPP) to feed the building blocks and the antioxidant responses of rapidly proliferating cells. In addition to the well-acknowledged cytosolic pathway, cancer cells also run a largely independent PPP, triggered by hexose-6P-dehydrogenase within the endoplasmic reticulum (ER), whose activity is mandatory for the integrity of ER–mitochondria networking. To verify whether this reticular metabolism is dependent on glutamine levels, we complemented the metabolomic characterization of intermediates of the glucose metabolism and tricarboxylic acid cycle with the estimation of proliferating activity, energy metabolism, redox damage, and mitochondrial function in two breast cancer cell lines. ER-PPP activity and its determinants were estimated by the ER accumulation of glucose analogs. Glutamine shortage decreased the proliferation rate despite increased ATP and NADH levels. It depleted NADPH reductive power and increased malondialdehyde content despite a marked increase in glucose-6P-dehydrogenase. This paradox was explained by the deceleration of ER-PPP favored by the decrease in hexose-6P-dehydrogenase expression coupled with the opposite response of its competitor enzyme glucose-6P-phosphatase. The decreased ER-PPP activity eventually hampered mitochondrial function and calcium exchanges. These data configure the ER-PPP as a powerful, unrecognized regulator of cancer cell metabolism and proliferation.

Large amounts of data from microbiome-related studies have been (and are currently being) deposited on international public databases. These datasets represent a valuable resource for the microbiome research community and could serve future researchers interested in integrating multiple datasets into powerful meta-analyses. However, this huge amount of data lacks harmonization and it is far from being completely exploited in its full potential to build a foundation that places microbiome research at the nexus of many subdisciplines within and beyond biology. Thus, it urges the need for data accessibility and reusability, according to findable, accessible, interoperable and reusable (FAIR) principles, as supported by National Microbiome Data Collaborative and FAIR Microbiome. To tackle the challenge of accelerating discovery and advances in skin microbiome research, we collected, integrated and organized existing microbiome data resources from human skin 16S rRNA amplicon-sequencing experiments. We generated a comprehensive collection of datasets, enriched in metadata, and organized this information into data frames ready to be integrated into microbiome research projects and advanced post-processing analyses, such as data science applications (e.g. machine learning). Furthermore, we have created a data retrieval and curation framework built on three different stages to maximize the retrieval of datasets and metadata associated with them. Lastly, we highlighted some caveats regarding metadata retrieval and suggested ways to improve future metadata submissions. Overall, our work resulted in a curated skin microbiome datasets collection accompanied by a state-of-the-art analysis of the last 10 years of the skin microbiome field. Database URL:  https://github.com/giuliaago/SKIOMEMetadataRetrieval.

Breast cancer (BC) is a heterogeneous disease, affecting millions of women every year. Early diagnosis is crucial to increasing survival. The clinical workup of BC diagnosis involves diagnostic imaging and bioptic characterization. In recent years, technical advances in image processing allowed for the application of advanced image analysis (radiomics) to clinical data. Furthermore, -omics technologies showed their potential in the characterization of BC. Combining information provided by radiomics with –omics data can be important to personalize diagnostic and therapeutic work up in a clinical context for the benefit of the patient. In this review, we analyzed the recent literature, highlighting innovative approaches to combine imaging and biochemical/biological data, with the aim of identifying recent advances in radiogenomics applied to BC. The results of radiogenomic studies are encouraging approaches in a clinical setting. Despite this, as radiogenomics is an emerging area, the optimal approach has to face technical limitations and needs to be applied to large cohorts including all the expression profiles currently available for BC subtypes (e.g., besides markers from transcriptomics, proteomics and miRNomics, also other non-coding RNA profiles).

Modern society grew rapidly over the last few decades and this led to an alarming increase in air pollutants and a worsening of the human health, especially in relation to the respiratory system. Indeed, chronic respiratory diseases were the third main cause of death in 2017, with over 3 million of deaths. Furthermore, the pollution has considerable consequences both for burden medical expenses and environmental. However, the mechanisms linking pollutants to the onset of these diseases remain unclear. Thus, in this study we addressed this problem through the United Kingdom BioBank database, analyzing 170 genome-wide association studies (103 related to respiratory diseases and 67 related to pollutants). We analyzed the genetic correlations and causal relationships of these traits, leveraging the summary statistics and bioinformatics packages such as Linkage Disequilibrium Score Regression and Latent Causal Variable. We obtained 158 significant genetic correlations and subsequently we analyzed them through the Latent Causal Variable analysis, obtaining 20 significant causal relationships. The most significant were between "Workplace full of chemicals or other fumes: Sometimes" and “Condition that has ever been diagnosed by a doctor: Asthma” and between “Workplace very dusty: Sometimes” and “Condition that has ever been diagnosed by a doctor: Emphysema or chronic bronchitis”. Finally, we identified single nucleotide polymorphisms independently associated with sveral pollutants to analyze the genes and pathways that could be involved in the onset of the aforementioned respiratory system disorders and that could be useful clinical target. This study highlighted how crucial are the air condition of the working environments and the type of transport used in the onset of respiratory-related morbidity. Based on that, we also suggested some interventions, in order to improve quality life and develop new and eco-friendly society and life style, such as improving indoor air cir

The industrial relevance of organic acids is high; because of their chemical properties, they can be used as building blocks as well as single-molecule agents with a huge annual market. Organic acid chemical platforms can derive from fossil sources by petrochemical refining processes, but most of them also represent natural metabolites produced by many cells. They are the products, by-products or co-products of many primary metabolic processes of microbial cells. Thanks to the potential of microbial cell factories and to the development of industrial biotechnology, from the last decades of the previous century, the microbial-based production of these molecules has started to approach the market. This was possible because of a joint effort of microbial biotechnologists and biochemical and process engineers that boosted natural production up to the titer, yield and productivity needed to be industrially competitive. More recently, the possibility to utilize renewable residual biomasses as feedstock not only for biofuels, but also for organic acids production is further augmenting the sustainability of their production, in a logic of circular bioeconomy. In this review, we briefly present the latest updates regarding the production of some industrially relevant organic acids (citric, fumaric, itaconic, lactic and succinic acid), discussing the challenges and possible future developments of successful production.

Sporadic Alzheimer’s disease (AD) is a complex neurological disorder characterized by many risk loci with potential associations with different traits and diseases. AD, characterized by a progressive loss of neuronal functions, manifests with different symptoms such as decline in memory, movement, coordination, and speech. The mechanisms underlying the onset of AD are not always fully understood, but involve a multiplicity of factors. Early diagnosis of AD plays a central role as it can offer the possibility of early treatment, which can slow disease progression. Currently, the methods of diagnosis are cognitive testing, neuroimaging, or cerebrospinal fluid analysis that can be time-consuming, expensive, invasive, and not always accurate. In the present study, we performed a genetic correlation analysis using genome-wide association statistics from a large study of AD and UK Biobank, to examine the association of AD with other human traits and disorders. In addition, since hippocampus, a part of cerebral cortex could play a central role in several traits that are associated with AD; we analyzed the gene expression profiles of hippocampus of AD patients applying 4 different artificial neural network models. We found 65 traits correlated with AD grouped into 9 clusters: medical conditions, fluid intelligence, education, anthropometric measures, employment status, activity, diet, lifestyle, and sexuality. The comparison of different 4 neural network models along with feature selection methods on 5 Alzheimer’s gene expression datasets showed that the simple basic neural network model obtains a better performance (66% of accuracy) than other more complex methods with dropout and weight regularization of the network.

The design of alternative biodegradable polymers has the potential of severely reducing the environmental impact, cost and production time currently associated with the petrochemical industry. In fact, growing demand for renewable feedstock has recently brought to the fore synthetic biology and metabolic engineering. These two interdependent research areas focus on the study of microbial conversion of organic acids, with the aim of replacing their petrochemical-derived equivalents with more sustainable and efficient processes. The particular case of Lactic acid (LA) production has been the subject of extensive research because of its role as an essential component for developing an eco-friendly biodegradable plastic—widely used in industrial biotechnological applications. Because of its resistance to acidic environments, among the many LA-producing microbes, Saccharomyces cerevisiae has been the main focus of research into related biocatalysts. In this study, we present an extensive in silico investigation of S. cerevisiae cell metabolism (modeled with Flux Balance Analysis) with the overall aim of maximizing its LA production yield. We focus on the yeast 8.3 steady-state metabolic model and analyze it under the impact of different engineering strategies including: gene knock-in, gene knock-out, gene regulation and medium optimization; as well as a comparison between results in aerobic and anaerobic conditions. We designed ad-hoc constrained multiobjective evolutionary algorithms to automate the engineering process and developed a specific postprocessing methodology to analyze the genetic manipulation results obtained. The in silico results reported in this paper empirically show that our method is able to automatically select a small number of promising genetic and metabolic manipulations, deriving competitive strains that promise to impact microorganisms design in the production of sustainable chemicals.

Leveraging genome-wide association statistics generated from a large study of amyotrophic lateral sclerosis (ALS; 29,612 cases and 122,656 controls) and UK Biobank (UKB; 4,024 phenotypes, up to 361,194 participants), we conducted a phenome-wide analysis of ALS genetic liability and identified 46 genetically correlated traits, such as fluid intelligence score (rg = − 0.21, p = 1.74 × 10–6), "spending time in pub or social club” (rg = 0.24, p = 2.77 × 10–6), non-work related walking (rg = − 0.25, p = 1.95 × 10–6), college education (rg = − 0.15, p = 7.08 × 10–5), “ever diagnosed with panic attacks (rg = 0.39, p = 4.24 × 10–5), and “self-reported other gastritis including duodenitis” (rg = 0.28, p = 1.4 × 10–3). To assess the putative directionality of these genetic correlations, we conducted a latent causal variable analysis, identifying significant genetic causality proportions (gĉp) linking ALS genetic liability to seven traits. While the genetic component of “self-reported other gastritis including duodenitis" showed a causal effect on ALS (gĉp = 0.50, p = 1.26 × 10–29), the genetic liability to ALS is potentially causal for multiple traits, also including an effect on "ever being diagnosed with panic attacks” (gĉp = 0.79, p = 5.011 × 10–15) and inverse effects on “other leisure/social group activities” (gĉp = 0.66, p = 1 × 10–4) and prospective memory result (gĉp = 0.35, p = 0.005). Our subsequent Mendelian randomization analysis indicated that some of these associations may be due to bidirectional effects. In conclusion, this phenome-wide investigation of ALS polygenic architecture highlights the widespread pleiotropy linking this disorder with several health domains.

Polystyrene is a thermoplastic polymer widely used in commercial products. Like all plastics, polystyrene can be degraded into microplastic and nanoplastic particles and ingested via food chain contamination. Although the ecological impact due to plastic contamination is well known, there are no studies indicating a carcinogenic potential of polystyrene microplastics (MPs) and nanoplastics (NPs). Here, we evaluated the effects of the MPs and NPs on normal human intestinal CCD-18Co cells. Our results show that internalization of NPs and MPs induces metabolic changes under both acute and chronic exposure by inducing oxidative stress, increasing glycolysis via lactate to sustain energy metabolism and glutamine metabolism to sustain anabolic processes. We also show that this decoupling of nutrients mirrors the effect of the potent carcinogenic agent azoxymethane and HCT15 colon cancer cells, carrying out the typical strategy of cancer cells to optimize nutrients utilization and allowing metabolic adaptation to environmental stress conditions. Taken together our data provide new evidence that chronic NPs and MPs exposure could act as cancer risk factor for human health.

Prostate cancer (PC) is a male common neoplasm and is the second leading cause of cancer death in American men. PC is traditionally diagnosed by the evaluation of prostate secreted antigen (PSA) in the blood. Due to the high levels of false positives, digital rectal examination and transrectal ultrasound guided biopsy are necessary in uncertain cases with elevated PSA levels. Nevertheless, the high mortality rate suggests that new PC biomarkers are urgently needed to help clinical diagnosis. In a previous study, we have identified a network of genes, altered in high Gleason Score (GS) PC (GS ≥ 7), being regulated by miR‐153. Until now, no publication has explained the mechanism of action of miR‐153 in PC. By in vitro studies, we found that the overexpression of miR‐ 153 in high GS cell lines is required to control cell proliferation, migration and invasion rates, targeting Kruppel‐like factor 5 (KLF5). Moreover, miR‐153 could be secreted by exosomes and microvesicles in the microenvironment and, once entered into the surrounding tissue, could influence cellular growth. Being upregulated in high GS human PC, miR‐153 could be proposed as a circulating biomarker for PC diagnosis.

Alzheimer’s disease (AD) is a neurodegenerative disease characterized by rapid brain cell degeneration affecting different areas of the brain. Hippocampus is one of the earliest involved brain regions in the disease. Modern technologies based on high-throughput data have identified transcriptional profiling of several neurological diseases, including AD, for a better comprehension of genetic mechanisms of the disease. In this study, we investigated differentially expressed genes (DEGs) from six Gene Expression Omnibus (GEO) datasets of hippocampus of AD patients. The identified DEGs were submitted to Weighted correlation network analysis (WGCNA) and ClueGo to explore genes with a higher degree centrality and to comprehend their biological role. Subsequently, MCODE was used to identify subnetworks of interconnected DEGs. Our study found 40 downregulated genes and 36 up-regulated genes as consensus DEGs. Analysis of the co-expression network revealed ACOT7, ATP8A2, CDC42, GAD1, GOT1, INA, NCALD, and WWTR1 to be genes with a higher degree centrality. ClueGO revealed the pathways that were mainly enriched, such as clathrin coat assembly, synaptic vesicle endocytosis, and DNA damage response signal transduction by p53 class mediator. In addition, we found a subnetwork of 12 interconnected genes (AMPH, CA10, CALY, NEFL, SNAP25, SNAP91, SNCB, STMN2, SV2B, SYN2, SYT1, and SYT13). Only CA10 and CALY are targets of known drugs while the others could be potential novel drug targets.

Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease characterized by the neurodegeneration of motoneurons. About 10% of ALS is hereditary and involves mutation in 25 different genes, while 90% of the cases are sporadic forms of ALS (sALS). The diagnosis of ALS includes the detection of early symptoms and, as disease progresses, muscle twitching and then atrophy spreads from hands to other parts of the body. The disease causes high disability and has a high mortality rate; moreover, the therapeutic approaches for the pathology are not effective. miRNAs are small non-coding RNAs, whose activity has a major impact on the expression levels of coding mRNA. The literature identifies several miRNAs with diagnostic abilities on sALS, but a unique diagnostic profile is not defined. As miRNAs could be secreted, the identification of specific blood miRNAs with diagnostic ability for sALS could be helpful in the identification of the patients. In the view of personalized medicine, we performed a meta-analysis of the literature in order to select specific circulating miRNAs with diagnostic properties and, by bioinformatics approaches, we identified a panel of 10 miRNAs (miR-193b, miR-3911, miR-139-5p, miR-193b-1, miR-338-5p, miR-3911-1, miR-455-3p, miR-4687-5p, miR-4745-5p, and miR-4763-3p) able to classify sALS patients by blood analysis. Among them, the analysis of expression levels of the couple of blood miR-193b/miR-4745-5p could be translated in clinical practice for the diagnosis of sALS.

Microorganisms offer a tremendous potential as cell factories, and they are indeed been used by humans since the previous centuries for biotransformations. Among them, yeasts combine the advantage of a unicellular state with a eukaryotic organization. Moreover, in the era of biorefineries, their biodiversity can offer solutions to specific process constraints. Zygosaccharomyces bailii, an ascomycete budding yeast, is widely known for its peculiar tolerance to different stresses, among which are organic acids. Moreover, the recent reclassification of the species, including diverse hybrids, is further expanding both fundamental and applied interests. It is therefore reasonable that despite the possibility to apply with this yeast some of the molecular tools and protocols routinely used to manipulate Saccharomyces cerevisiae, adjustments and optimizations are necessary. Here we describe in detail the methods for determining chromosome number, size, and aneuploidy, transformation, classical target gene disruption or gene integration, and designing of episomal expression plasmids helpful for engineering the yeast Z. bailii .

Background: Omega-3 fatty acids (FAs) are relevant commodities in the market due to their important role in human wellbeing. As the worldwide demand is increasing, alternative sources and sustainable processes are needed to face the limited supply of the omega-3 FAs of fish origin. Microalgae provide a portfolio of biodiversity able to satisfy the quest for alternative sources and to match the need of sustainability for the production of these compounds. Scope and approach: This review deepens the topic of sustainable production and supply chain by analyzing the current data available in scientific literature and providing a glance of the market of omega-3 FAs from different microalgal species. This was assessed in the light of the technologies applicable to enhance and improve production. We analyzed and compared how traditional and innovative biotechnological approaches are exploited to maximize the ability of microalgae to produce omega-3 FAs, especially eicosapentaenoic acid and docosahexaenoic acid (EPA and DHA). Key findings and conclusions: This critical overview highlights that microalgal bioprospecting, combined with engineering approaches and with the study of the influence from the environment, can provide a reliable and sustainable alternative for omega-3 FAs production. Unlocking the interdependence of these factors will play a key role in achieving the industrial scalability and standardization of the processes. Finally, the strategy to promote the consumer's acceptability of algae-based products will also be pivotal to substitute the current sources of omega-3 FAs and therefore to address the sustainability challenges that Europe, as well as the rest of the world, is facing.

Background: Lipids from oleaginous yeasts emerged as a sustainable alternative to vegetable oils and animal fat to produce biodiesel, the biodegradable and environmentally friendly counterpart of petro-diesel fuel. To develop economically viable microbial processes, the use of residual feedstocks as growth and production substrates is required. Results: In this work we investigated sugar beet pulp (SBP) and molasses, the main residues of sugar beet processing, as sustainable substrates for the growth and lipid accumulation by the oleaginous yeast Lipomyces starkeyi. We observed that in hydrolysed SBP the yeast cultures reached a limited biomass, cellular lipid content, lipid production and yield (2.5 g/L, 19.2%, 0.5 g/L and 0.08 g/g, respectively). To increase the initial sugar availability, cells were grown in SBP blended with molasses. Under batch cultivation, the cellular lipid content was more than doubled (47.2%) in the presence of 6% molasses. Under pulsed-feeding cultivation, final biomass, cellular lipid content, lipid production and lipid yield were further improved, reaching respectively 20.5 g/L, 49.2%, 9.7 g/L and 0.178 g/g. Finally, we observed that SBP can be used instead of ammonium sulphate to fulfil yeasts nitrogen requirement in molasses-based media for microbial oil production. Conclusions: This study demonstrates for the first time that SBP and molasses can be blended to create a feedstock for the sustainable production of lipids by L. starkeyi. The data obtained pave the way to further improve lipid production by designing a fed-batch process in bioreactor. Graphical abstract: [Figure not available: see fulltext.]

We describe the procedures to perform the following: (1) the de novo discovery of mutational signatures from raw sequencing data of viral samples and (2) the association of existing viral mutational signatures to the samples of a given dataset. The goal is to identify and characterize the nucleotide substitution patterns related to the mutational processes that underlie the origination of variants in viral genomes. The VirMutSig protocol is available at this link: https://github.com/BIMIB-DISCo/VirMutSig. For complete information on the theoretical aspects of this protocol, please refer to Graudenzi et al. (2021).

Several compounds on the market derive from petrochemical synthesis, and carotenoids are no exception. Nonetheless, since their applications in the food, feed and cosmetic sectors, and because of sustainability issues, carotenoids of natural origin are desirable. Carotenoids can be extracted from several plants but also from carotenogenic microorganisms, among which are yeasts. Nonetheless, to meet sustainability criteria, the substrate used for yeast cultivation has to be formulated from residual biomasses. For these reasons, we deploy the yeast, Rhodosporidium toruloides, to obtain carotenoids from Camelina sativa meal, an underrated lignocellulosic biomass. Its enzymatic hydrolysis ensures the release of the sugars, as well as of the other nutrients necessary to sustain the process. We therefore separately optimized enzymatic and biomass loadings, and calculated the yields and productivities of the obtained carotenoids. The best conditions (9% w/v biomass, 0.56% w/wbiomass enzymes) were tested in different settings, in which the fermentation was performed separately or simultaneously with hydrolysis, resulting in a similar production of carotenoids. In order to collect quantitative data under controlled chemo-physical parameters, the process was implemented in stirred-tank bioreactors, obtaining 3.6 ± 0.69 mg/L of carotenoids; despite the volumetric and geometric change, the outcomes were consistent with results from the fermentation of shake flasks. Therefore, these data pave the way to evaluate a potential future industrialization of this bioprocess, considering the opportunity to optimize the use of different amounts of biomass and enzyme loading, as well as the robustness of the process in the bioreactor.

Background As the circular economy advocates a near total waste reduction, the industry has shown an increased interest toward the exploitation of various residual biomasses. The origin and availability of biomass used as feedstock strongly affect the sustainability of biorefineries, where it is converted in energy and chemicals. Here, we explored the valorization of Camelina meal, the leftover residue from Camelina sativa oil extraction. In fact, in addition to Camelina meal use as animal feed, there is an increasing interest in further valorizing its macromolecular content or its nutritional value. Results Camelina meal hydrolysates were used as nutrient and energy sources for the fermentation of the carotenoid-producing yeast Rhodosporidium toruloides in shake flasks. Total acid hydrolysis revealed that carbohydrates accounted for a maximum of 31 +/- 1.0% of Camelina meal. However, because acid hydrolysis is not optimal for subsequent microbial fermentation, an enzymatic hydrolysis protocol was assessed, yielding a maximum sugar recovery of 53.3%. Separate hydrolysis and fermentation (SHF), simultaneous saccharification and fermentation (SSF), and SSF preceded by presaccharification of Camelina meal hydrolysate produced 5 +/- 0.7, 16 +/- 1.9, and 13 +/- 2.6 mg/L of carotenoids, respectively. Importantly, the presence of water-insoluble solids, which normally inhibit microbial growth, correlated with a higher titer of carotenoids, suggesting that the latter could act as scavengers. Conclusions This study paves the way for the exploitation of Camelina meal as feedstock in biorefinery processes. The process under development provides an example of how different final products can be obtained from this side stream, such as pure carotenoids and carotenoid-enriched Camelina meal, can potentially increase the initial value of the source material. The obtained data will help assess the feasibility of using Camelina meal to generate high value-added products.

La necessità di sviluppare processi sostenibili trova nelle trasformazioni di biomasse di scarto un’alternativa tanto promettente quanto ambiziosa. Questa sfida è raccolta da Galatea Biotech Srl, PMI innovativa operante nel settore delle bioplastiche ed impegnata nello sviluppo di materiali biobased e biodegradabili attraverso fermentazioni microbiche.