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Abstract Background Macroalgae, especially reds (Rhodophyta Division) and browns (Phaeophyta Division), are known for producing various halogenated compounds. Yet, the reasons underlying their production and the fate of these metabolites remain largely unknown. Some theories suggest their potential antimicrobial activity and involvement in interactions between macroalgae and prokaryotes. However, detailed investigations are currently missing on how the genetic information of prokaryotic communities associated with macroalgae may influence the fate of organohalogenated molecules. Results To address this challenge, we created a specialized dataset containing 161 enzymes, each with a complete enzyme commission number, known to be involved in halogen metabolism. This dataset served as a reference to annotate the corresponding genes encoded in both the metagenomic contigs and 98 metagenome-assembled genomes (MAGs) obtained from the microbiome of 2 red (Sphaerococcus coronopifolius and Asparagopsis taxiformis) and 1 brown (Halopteris scoparia) macroalgae. We detected many dehalogenation-related genes, particularly those with hydrolytic functions, suggesting their potential involvement in the degradation of a wide spectrum of halocarbons and haloaromatic molecules, including anthropogenic compounds. We uncovered an array of degradative gene functions within MAGs, spanning various bacterial orders such as Rhodobacterales, Rhizobiales, Caulobacterales, Geminicoccales, Sphingomonadales, Granulosicoccales, Microtrichales, and Pseudomonadales. Less abundant than degradative functions, we also uncovered genes associated with the biosynthesis of halogenated antimicrobial compounds and metabolites. Conclusion The functional data provided here contribute to understanding the still largely unexplored role of unknown prokaryotes. These findings support the hypothesis that macroalgae function as holobionts, where the metabolism of halogenated compounds might play a role in symbiogenesis and act as a possible defense mechanism against environmental chemical stressors. Furthermore, bacterial groups, previously never connected with organohalogen metabolism, e.g., Caulobacterales, Geminicoccales, Granulosicoccales, and Microtrichales, functionally characterized through MAGs reconstruction, revealed a biotechnologically relevant gene content, useful in synthetic biology, and bioprospecting applications. Video Abstract

Metagenomics, Metabolomics, and Metaproteomics have significantly advanced our knowledge of microbial communities by providing culture-independent insights into their composition and functional potential. However, a critical challenge in this field is the lack of standard and comprehensive metadata associated with raw data, hindering the ability to perform robust data stratifications and consider confounding factors. In this comprehensive review, we categorize publicly available microbiome data into five types: shotgun sequencing, amplicon sequencing, metatranscriptomic, metabolomic, and metaproteomic data. We explore the importance of metadata for data reuse and address the challenges in collecting standardized metadata. We also, assess the limitations in metadata collection of existing public repositories collecting metagenomic data. This review emphasizes the vital role of metadata in interpreting and comparing datasets and highlights the need for standardized metadata protocols to fully leverage metagenomic data's potential. Furthermore, we explore future directions of implementation of Machine Learning (ML) in metadata retrieval, offering promising avenues for a deeper understanding of microbial communities and their ecological roles. Leveraging these tools will enhance our insights into microbial functional capabilities and ecological dynamics in diverse ecosystems. Finally, we emphasize the crucial metadata role in ML models development.

Identifying farming practices that decrease susceptibility to infectious diseases and optimise food conversion efficiency is valuable for chicken welfare and productivity, the environment, and public health. Enterotypes can be used to define microbial community phenotypes that have differential, potentially significant impacts on gut health. In this study, we delineated enterotypes by analysing the microbiomes of 300 indigenous Kadaknath and 300 commercial Cobb400 broiler chickens raised across 60 farms in western India. Using a compositional data approach, we identified three distinct enterotypes: PA1 (n=290), PA2 (n=142) and PA3 (n=67). PA1 and PA2 clustered more closely with each other than with PA3, however, PA2 had significantly lower alpha diversity than PA1. PA1 had a high Firmicutes: Bacteroides ratio, was dominated by Faecalibacterium and had a higher abundance of Prevotellamassilia than other enterotypes. PA2 was characterised by its low alpha diversity, a high abundance of the common taxa Phascolarctobacterium A and Phocaeicola dorei and a significantly higher Campylobacter abundance than PA1. PA3 had the highest Bacteroidota abundance of the three enterotypes and was defined by high prevalence of lower abundance taxa such as CAG-831 and Mucispirillum schaedleri. Network analysis showed that all enterotypes have different proportions of competing Firmicutes-dominant and Bacteroidota-dominant guilds. Random Forest Modelling using defined farm characteristics was predictive for enterotype. Factors affecting enterotype include whether farms were open, enclosed or caged, the location of farms, whether visitors were allowed inside, the number of people in contact with the chickens, chicken line, the presence of dogs and whether flock thinning took place. This study suggests that enterotypes are influenced by farming practices, hence modification of practices could potentially be used to reduce the burden of zoonotic pathogens such as Campylobacter.

Abstract To date several studies address the important role of gut microbiome and its interplay with the human host in the health and disease status. However, the selection of a universal sampling matrix representative of the microbial biodiversity associated with the gastrointestinal (GI) tract, is still challenging. Here we present a study in which, through a deep metabarcoding analysis of the 16S rRNA gene, we compared two sampling matrices, feces (F) and colon washing feces (CWF), in order to evaluate their relative effectiveness and accuracy in representing the complexity of the human gut microbiome. A cohort of 30 volunteers was recruited and paired F and CWF samples were collected from each subject. Alpha diversity analysis confirmed a slightly higher biodiversity of CWF compared to F matched samples. Likewise, beta diversity analysis proved that paired F and CWF microbiomes were quite similar in the same individual, but remarkable inter-individual variability occurred among the microbiomes of all participants. Taxonomic analysis in matched samples was carried out to investigate the intra and inter individual/s variability. Firmicutes, Bacteroidota, Proteobacteria and Actinobacteriota were the main phyla in both F and CWF samples. At genus level, Bacteirodetes was the most abundant in F and CWF samples, followed by Faecalibacterium, Blautia and Escherichia-Shigella. Our study highlights an inter-individual variability greater than intra-individual variability for paired F and CWF samples. Indeed, an overall higher similarity was observed across matched F and CWF samples, suggesting, as expected, a remarkable overlap between the microbiomes inferred using the matched F and CWF samples. Notably, absolute quantification of total 16S rDNA by droplet digital PCR (ddPCR) revealed comparable overall microbial load between paired F and CWF samples. We report here the first comparative study on fecal and colon washing fecal samples for investigating the human gut microbiome and show that both types of samples may be used equally for the study of the gut microbiome. The presented results suggest that the combined use of both types of sampling matrices could represent a suitable choice to obtain a more complete overview of the human gut microbiota for addressing different biological and clinical questions.

Seahorses are small sedentary fish considered flagship species of the conservation efforts. They are particularly vulnerable to human pressures because inhabiting threatened coastal ecosystems. Indeed, the worldwide decline of local populations in the last decades led to the inclusion of all seahorse species on the IUCN Red List, where most species, including Hippocampus guttulatus, were classified as ‘‘Data Deficient’’ on a global level due to the lack of relative data on several biological and ecological traits. Because of such sensitive conservation status, improvement of the current knowledge on the diet composition of wild animals and its differences among habitats could be of great importance as it could help understanding the way the environment is exploited. In the present study, we used a non-invasive DNA metabarcoding technique to further elucidate long-snouted seahorse diet and expand our understanding of prey choice among different habitats. We identified 24 families, 22 genera and 26 species, and according to the results, most of the seahorse samples contained taxa such as Amphipoda, Decapoda, Isopoda, and Mysida. Several non-native species were discovered in the diet, suggesting their dietary incorporation that could mirror high anthropogenic impacts and habitat modifications. We found significant differences in the diet composition among investigated habitats, thus indicating trophic flexibility of H. guttulatus among diverse habitats, a characteristic that may be essential for the resilience of this iconic yet sensitive species.

Abstract Background Breast cancer (BC) is the most common malignancy in women, in whom it reaches 20% of the total neoplasia incidence. Most BCs are considered sporadic and a number of factors, including familiarity, age, hormonal cycles and diet, have been reported to be BC risk factors. Also the gut microbiota plays a role in breast cancer development. In fact, its imbalance has been associated to various human diseases including cancer although a consequential cause-effect phenomenon has never been proven. Methods The aim of this work was to characterize the breast tissue microbiome in 34 women affected by BC using an NGS-based method, and analyzing the tumoral and the adjacent non-tumoral tissue of each patient. Results The healthy and tumor tissues differed in bacterial composition and richness: the number of Amplicon Sequence Variants (ASVs) was higher in healthy tissues than in tumor tissues (p = 0.001). Moreover, our analyses, able to investigate from phylum down to species taxa for each sample, revealed major differences in the two richest phyla, namely, Proteobacteria and Actinobacteria. Notably, the levels of Actinobacteria and Proteobacteria were, respectively, higher and lower in healthy with respect to tumor tissues. Conclusions Our study provides information about the breast tissue microbial composition, as compared with very closely adjacent healthy tissue (paired samples within the same woman); the differences found are such to have possible diagnostic and therapeutic implications; further studies are necessary to clarify if the differences found in the breast tissue microbiome are simply an association or a concausative pathogenetic effect in BC. A comparison of different results on similar studies seems not to assess a universal microbiome signature, but single ones depending on the environmental cohorts’ locations.

The 16S rRNA amplicon-based sequencing approach represents the most common and cost-effective strategy with great potential for microbiome profiling. The use of second-generation sequencing (NGS) technologies has led to protocols based on the amplification of one or a few hypervariable regions, impacting the outcome of the analysis. Nowadays, comparative studies are necessary to assess different amplicon-based approaches, including the full-locus sequencing currently feasible thanks to third-generation sequencing (TGS) technologies. This study compared three different methods to achieve the deepest microbiome taxonomic characterization: (a) the single-region approach, (b) the multiplex approach, covering several regions of the target gene/region, both based on NGS short reads, and (c) the full-length approach, which analyzes the whole length of the target gene thanks to TGS long reads. Analyses carried out on benchmark microbiome samples, with a known taxonomic composition, highlighted a different classification performance, strongly associated with the type of hypervariable regions and the coverage of the target gene. Indeed, the full-length approach showed the greatest discriminating power, up to species level, also on complex real samples. This study supports the transition from NGS to TGS for the study of the microbiome, even if experimental and bioinformatic improvements are still necessary.

Oranger et al use digital droplet PCR to develop an assay that provides a dynamic snapshot of the levels of SARS-CoV-2 sub-genomic messanger RNA in infected individuals. This has the potential to improve diagnostic accuracy for COVID-19

Microbial stability of fresh pasta depends on heat treatment, storage temperature, proper preservatives, and atmosphere packaging. This study aimed at improving the microbial quality, safety, and shelf life of fresh pasta using modified atmosphere composition and packaging with or without the addition of bioprotective cultures (Lactobacillus acidophilus, Lactobacillus casei, Bifidobacterium spp., and Bacillus coagulans) into semolina. Three fresh pasta variants were made using (i) the traditional protocol (control), MAP (20:80 CO2:N2), and barrier packaging, (ii) the experimental MAP (40:60 CO2:N2) and barrier packaging, and (iii) the experimental MAP, barrier packaging, and bioprotective cultures. Their effects on physicochemical properties (i.e., content on macro elements, water activity, headspace O2, CO2 concentrations, and mycotoxins), microbiological patterns, protein, and volatile organic compounds (VOC) were investigated at the beginning and the end of the actual or extended shelf-life through traditional and multi-omics approaches. We showed that the gas composition and properties of the packaging material tested in the experimental MAP system, with or without bioprotective cultures, positively affect features of fresh pasta avoiding changes in their main chemical properties, allowing for a storage longer than 120 days under refrigerated conditions. These results support that, although bioprotective cultures were not all able to grow in tested conditions, they can control the spoilage and the associated food-borne microbiota in fresh pasta during storage by their antimicrobials and/or fermentation products synergically. The VOC profiling, based on gas-chromatography mass-spectrometry (GC-MS), highlighted significant differences affected by the different manufacturing and packaging of samples. Therefore, the use of the proposed MAP system and the addition of bioprotective cultures can be considered an industrial helpful strategy to reduce the quality loss during refrigerated storage and to increase the shelf life of fresh pasta for additional 30 days by allowing the economic and environmental benefits spurring innovation in existing production models.

Background and aims The role of inflammatory immune responses in colorectal cancer (CRC) development and response to therapy is a matter of intense debate. While inflammation is a known driver of CRC, inflammatory immune infiltrates are a positive prognostic factor in CRC and predispose to response to immune checkpoint blockade (ICB) therapy. Unfortunately, over 85% of CRC cases are primarily unresponsive to ICB due to the absence of an immune infiltrate, and even the cases that show an initial immune infiltration can become refractory to ICB. The identification of therapy supportive immune responses in the field has been partially hindered by the sparsity of suitable mouse models to recapitulate the human disease. In this study, we aimed to understand how the dysregulation of the complement anaphylatoxin C3a receptor (C3aR), observed in subsets of patients with CRC, affects the immune responses, the development of CRC, and response to ICB therapy.Methods We use a comprehensive approach encompassing analysis of publicly available human CRC datasets, inflammation-driven and newly generated spontaneous mouse models of CRC, and multiplatform high-dimensional analysis of immune responses using microbiota sequencing, RNA sequencing, and mass cytometry.Results We found that patients’ regulation of the complement C3aR is associated with epigenetic modifications. Specifically, downregulation of C3ar1 in human CRC promotes a tumor microenvironment characterized by the accumulation of innate and adaptive immune cells that support antitumor immunity. In addition, in vivo studies in our newly generated mouse model revealed that the lack of C3a in the colon activates a microbiota-mediated proinflammatory program which promotes the development of tumors with an immune signature that renders them responsive to the ICB therapy.Conclusions Our findings reveal that C3aR may act as a previously unrecognized checkpoint to enhance antitumor immunity in CRC. C3aR can thus be exploited to overcome ICB resistance in a larger group of patients with CRC.

The intestinal tract hosts the gut microbiota (GM), actively shaping health. Bile acids(BAs) are both digestive and signaling molecules acting as hormones via the activation of farnesoid X receptor (FXR). Obstruction of bile flow initiates a cascade of pathological events ultimately leading to intestinal mucosal injury. Administration of BAs in models of obstructed bile flow counteracts these detrimental effects. Objective of this study was to investigate the effects of the novel FXR agonist 3α, 7α, 11β-Trihydroxy-6α-ethyl-5β-cholan-24-oic Acid (TC-100) on intestinal mucosa integrity and cecal microbiome composition after surgical bile duct ligation (BDL), a rodent model causing bile flow obstruction.Pharmacological FXR activation was accomplished by daily oral gavage with TC-100 for 5 days. 2 days after treatment initiation, BDL was performed. BAs measurement was carried out and the 16S rDNA (V5-V6 hyper-variable regions) extracted from the cecal content was sequenced.TC-100 activates Fxr in the gut-liver axis and this translated into a significant reduction of serum and bile BA pool size with a shift to a more hydrophilic composition, while signs of intestinal mucosal damage were prevented. Firmicutes:Bacteroidota ratio progressively increased from Sham Operated (SO) mice to TC-100-treated mice. LEfSe analysis showed that Verrucomicrobia, and particularly Akkermansia muciniphila (Amuc) increasingly recognized for improving gut homeostasis and immune functions, were strongly associated to TC-100-treated mice. Intriguingly, Amuc abundance was also negatively associated to cholic acid levels.Collectively, these data indicate that intestinal FXR activation by TC-100 prevents early signs of intestinal mucosal damage by modulating BA homeostasis and GM composition.

High throughput sequencing technologies have enabled the study of complex biological aspects at single nucleotide resolution, opening the big data era. The analysis of large volumes of heterogeneous “omic” data, however, requires novel and efficient computational algorithms based on the paradigm of Artificial Intelligence. In the present review, we introduce and describe the most common machine learning methodologies, and lately deep learning, applied to a variety of genomics tasks, trying to emphasize capabilities, strengths and limitations through a simple and intuitive language. We highlight the power of the machine learning approach in handling big data by means of a real life example, and underline how described methods could be relevant in all cases in which large amounts of multimodal genomic data are available.

Bronchiolitis due to respiratory syncytial virus (RSV) or non-RSV agents is a health-menacing lower respiratory tract (LRT) disease of infants. Whereas RSV causes more severe disease than other viral agents may, genus-dominant fecal microbiota profiles have been identified in US hospitalized infants with bronchiolitis. We investigated the fecal microbiota composition of infants admitted to an Italian hospital with acute RSV (25/37 [67.6%]; group I) or non-RSV (12/37 [32.4%]; group II) bronchiolitis, and the relationship of fecal microbiota characteristics with the clinical characteristics of infants. Group I and group II infants differed significantly (24/25 [96.0%] versus 5/12 [41.7%]; P = 0.001) regarding 90% oxygen saturation (SpO2), which is an increased respiratory effort hallmark. Accordingly, impaired feeding in infants from group I was significantly more frequent than in infants from group II (19/25 [76.0%] versus 4/12 [33.3%]; P = 0.04). Conversely, the median (IQR) length of stay was not significantly different between the two groups (seven [3–14] for group I versus five [5–10] for group II; P = 0.11). The 16S ribosomal RNA V3–V4 region amplification of infants’ fecal samples resulted in 299 annotated amplicon sequence variants. Based on alpha- and beta-diversity microbiota downstream analyses, group I and group II infants had similar bacterial communities in their samples. Additionally, comparing infants having

In recent years, the involvement of the gut microbiota in disease and health has been investigated by sequencing the 16S gene from fecal samples. Dysbiotic gut microbiota was also observed in Autism Spectrum Disorder (ASD), a neurodevelopmental disorder characterized by gastrointestinal symptoms. However, despite the relevant number of studies, it is still difficult to identify a typical dysbiotic profile in ASD patients. The discrepancies among these studies are due to technical factors (i.e., experimental procedures) and external parameters (i.e., dietary habits). In this paper, we collected 959 samples from eight available projects (540 ASD and 419 Healthy Controls, HC) and reduced the observed bias among studies. Then, we applied a Machine Learning (ML) approach to create a predictor able to discriminate between ASD and HC. We tested and optimized three algorithms: Random Forest, Support Vector Machine and Gradient Boosting Machine. All three algorithms confirmed the importance of five different genera, including Parasutterella and Alloprevotella. Furthermore, our results show that ML algorithms could identify common taxonomic features by comparing datasets obtained from countries characterized by latent confounding variables.

Abstract Background Adenosine-to-inosine (A-to-I) RNA editing is an essential post-transcriptional mechanism mediated by ADAR enzymes that have been recently associated with cancer. Results Here, we characterize the inosinome signature in normal brain and de novo glioblastoma (GBM) using new metrics that re-stratify GBM patients according to their editing profiles and indicate this post-transcriptional event as a possible molecular mechanism for sexual dimorphism in GBM. We find that over 85% of de novo GBMs carry a deletion involving the genomic locus of ADAR3, which is specifically expressed in the brain. By analyzing RNA editing and patient outcomes, an intriguing gender-dependent link appears, with high editing of Alus shown to be beneficial only in male patients. We propose an inosinome-based molecular stratification of GBM patients that identifies two different GBM subgroups, INO-1 and INO-2, which can identify novel high-risk gender-specific patient groups for which more aggressive treatments may be necessary. Conclusions Our data provide a detailed picture of RNA editing landscape in normal brain and GBM, exploring A-to-I RNA editing regulation, disclosing unexpected editing implications for GBM patient stratification and identification of gender-dependent high-risk patients, and suggesting COG3 I/V as an eligible site for future personalized targeted gene therapy.

Seahorses are considered a flagship species for conservation efforts and due to their conservation status, improving knowledge on their dietary composition while applying a non-invasive approach, could be useful. Using Hippocampus guttulatus as a case study, the present study represents pioneering research into investigating the diet of seahorses by NGS-based DNA metabarcoding of fecal samples. The study developed and tested the protocol for fecal DNA metabarcoding during the feeding trials where captive seahorses were fed on a diet of known composition; the process was subsequently applied on fecal samples collected from wild individuals. The analysis of samples collected during the feeding trials indicated the reliability of the applied molecular approach by allowing the characterization of the effectively ingested prey. In the field study, among detected prey species, results revealed that the majority of the seahorse samples contained taxa such as Amphipoda, Decapoda, Isopoda, and Calanoida, while less common prey taxa were Gastropoda and Polyplacophora. As only a small amount of starting fecal material is needed and the sampling procedure is neither invasive nor lethal. The present study indicates DNA metabarcoding as useful for investigating seahorse diet and could help define management and conservation actions.

The ATP-gated ionotropic P2X7 receptor regulates T follicular helper (Tfh) cell abundance in the Peyer’s patches (PPs) of the small intestine; deletion of P2rx7, encoding for P2X7, in Tfh cells results in enhanced IgA secretion and binding to commensal bacteria. Here, we show that Tfh cell activity is important for generating a diverse bacterial community in the gut and that sensing of microbiota-derived extracellular ATP via P2X7 promotes the generation of a proficient gut ecosystem for metabolic homeostasis. The results of this study indicate that Tfh cells play a role in host-microbiota mutualism beyond protecting the intestinal mucosa by induction of affinity-matured IgA and suggest that extracellular ATP constitutes an inter-kingdom signaling molecule important for selecting a beneficial microbial community for the host via P2X7-mediated regulation of B cell help.

Colorectal cancer (CRC) initiation is believed to result from the conversion of normal intestinal stem cells (ISCs) into cancer stem cells (CSCs), also known as tumor-initiating cells (TICs). Hence, CRC evolves through the multiple acquisition of well-established genetic and epigenetic alterations with an adenoma-carcinoma sequence progression. Unlike other stem cells elsewhere in the body, ISCs cohabit with the intestinal microbiota, which consists of a diverse community of microorganisms, including bacteria, fungi, and viruses. The gut microbiota communicates closely with ISCs and mounting evidence suggests that there is significant crosstalk between host and microbiota at the ISC niche level. Metagenomic analyses have demonstrated that the host-microbiota mutually beneficial symbiosis existing under physiologic conditions is lost during a state of pathological microbial imbalance due to the alteration of microbiota composition (dysbiosis) and/or the genetic susceptibility of the host. The complex interaction between CRC and microbiota is at the forefront of the current CRC research, and there is growing attention on a possible role of the gut microbiome in the pathogenesis of CRC through ISC niche impairment. Here we primarily review the most recent findings on the molecular mechanism underlying the complex interplay between gut microbiota and ISCs, revealing a possible key role of microbiota in the aberrant reprogramming of CSCs in the initiation of CRC. We also discuss recent advances in OMICS approaches and single-cell analyses to explore the relationship between gut microbiota and ISC/CSC niche biology leading to a desirable implementation of the current precision medicine approaches.

Obesity and diet are associated with colorectal cancer (CRC) risk, and microbiome could mediate this risk factor. To investigate this interaction, we performed a case–control study (34 CRC cases and 32 controls) and analyzed fecal microbiota composition using 16S rRNA metabarcoding and sub-sequential shotgun analyses of genomic bacterial DNA to evaluate the role of microbiome and diet in CRC etiology, taking into account vitamin D and other risk biomarkers. Dietary habits were evaluated using a short questionnaire. Multivariate methods for data integration and mediation analysis models were used to investigate causal relationships. CRC cases were significantly more often deficient in vitamin D than controls (p = 0.04); FokI and CYP24A1 polymorphism frequency were different between cases and controls (p = 0.03 and p = 0.02, respectively). A diet poor in fatty fish and rich in carbohydrates was found to be significantly associated with CRC risk (p = 0.011). The mediation analysis confirmed the significant role of the microbiome in mediating CRC risk—increasing levels of Bifidobacteria/Escherichia genera ratio, an indicator of “healthy” intestinal microbiome, can overcome the effect of diet on CRC risk (p = 0.03). This study suggests that microbiome mediates the diet effect on CRC risk, and that vitamin D, markers of inflammation, and adipokines are other factors to consider in order to achieve a better knowledge of the whole carcinogenic process.

Gastric cancer (GC) is the fifth most prevalent cancer worldwide and the third leading cause of global cancer mortality. With the advances of the omic studies, a heterogeneous GC landscape has been revealed, with significant molecular diversity. Given the multifaceted nature of GC, identification of different patient subsets with prognostic and/or predictive outcomes is a key aspect to allow tailoring of specific treatments. Recently, the involvement of the microbiota in gastric carcinogenesis has been described. To deepen this aspect, we compared microbiota composition in signet-ring cell carcinoma (SRCC) and adenocarcinoma (ADC), two distinct GC subtypes. To this purpose, 10 ADC and 10 SRCC and their paired non-tumor (PNT) counterparts were evaluated for microbiota composition through 16S rRNA analysis. Weighted and unweighted UniFrac and Bray–Curtis dissimilarity showed significant community-level separation between ADC and SRCC. Through the LEfSe (linear discriminant analysis coupled with effect size) tool, we identified potential microbial biomarkers associated with GC subtypes. In particular, SRCCs were significantly enriched in the phyla Fusobacteria, Bacteroidetes, Patescibacteria, whereas in the ADC type, Proteobacteria and Acidobacteria phyla were found. Overall, our data add new insights into GC heterogeneity and may contribute to deepening the GC classification.

Jellyfish blooms are frequent and widespread in coastal areas worldwide, often associated with significant ecological and socio-economic consequences. Recent studies have also suggested cnidarian jellyfish may act as vectors of bacterial pathogens. The scyphomedusa Rhizostoma pulmo is an outbreak-forming jellyfish widely occurring across the Mediterranean basin. Using combination of culture-based approaches and a high-throughput amplicon sequencing (HTS), and based on available knowledge on a warm-affinity jellyfish-associated microbiome, we compared the microbial community associated with R. pulmo adult jellyfish in the Gulf of Taranto (Ionian Sea) between summer (July 2016) and winter (February 2017) sampling periods. The jellyfish-associated microbiota was investigated in three distinct compartments, namely umbrella, oral arms, and the mucus secretion. Actinobacteria, Bacteroidetes, Chlamydiae, Cyanobacteria, Deinococcus-Thermus, Firmicutes, Fusobacteria, Planctomycetes, Proteobacteria, Rhodothermaeota, Spirochaetes, Tenericutes, and Thaumarchaeota were the phyla isolated from all the three R. pulmo compartments in the sampling times. In particular, the main genera Mycoplasma and Spiroplasma, belonging to the class Mollicutes (phylum Tenericutes), have been identified in all the three jellyfish compartments. The taxonomic microbial data were coupled with metabolic profiles resulting from the utilization of 31 different carbon sources by the BIOLOG Eco-Plate system. Microorganisms associated with mucus are characterized by great diversity. The counts of culturable heterotrophic bacteria and potential metabolic activities are also remarkable. Results are discussed in terms of R. pulmo ecology, the potential health hazard for marine and human life as well as the potential biotechnological applications related to the associated microbiome.

Microorganisms inhabiting saline environments are an interesting ecological model for the study of the adaptation of organisms to extreme living conditions and constitute a precious resource of enzymes and bioproducts for biotechnological applications. We analyzed the microbial communities in nine ponds with increasing salt concentrations (salinity range 4.9–36.0%) of the Saltern of Margherita di Savoia (Italy), the largest thalassohaline saltern in Europe. A deep-metabarcoding NGS procedure addressing separately the V5-V6 and V3-V4 hypervariable regions of the 16S rRNA gene of Bacteria and Archaea, respectively, and a CARD-FISH (catalyzed reporter deposition fluorescence in situ hybridization) analysis allowed us to profile the dynamics of microbial populations at the different salt concentrations. Both the domains were detected throughout the saltern, even if the low relative abundance of Archaea in the three ponds with the lowest salinities prevented the construction of the relative amplicon libraries. The highest cell counts were recorded at 14.5% salinity for Bacteria and at 24.1% salinity for Archaea. While Bacteria showed the greatest number of genera in the first ponds (salinity range 4.9–14.5%), archaeal genera were more numerous in the last ponds of the saltern (salinity 24.1–36.0%). Among prokaryotes, Salinibacter was the genus with the maximum abundance (~49% at 34.6% salinity). Other genera detected at high abundance were the archaeal Haloquadratum (~43% at 36.0% salinity) and Natronomonas (~18% at 13.1% salinity) and the bacterial “Candidatus Aquiluna” (~19% at 14.5% salinity). Interestingly, “Candidatus Aquiluna” had not been identified before in thalassohaline waters.

Regulated mRNA translation plays a key role in control of cell cycle progression in a variety of physiological and pathological processes, including in the self-renewal and survival of stem cells and cancer stem cells. While targeting mRNA translation presents an attractive strategy for control of aberrant cell cycle progression, mRNA translation is an underdeveloped therapeutic target. Regulated mRNAs are typically controlled through interaction with multiple RNA binding proteins (RBPs) but the mechanisms by which the functions of distinct RBPs bound to a common target mRNA are coordinated are poorly understood. The challenge now is to gain insight into these mechanisms of coordination and to identify the molecular mediators that integrate multiple, often conflicting, inputs. A first step includes the identification of altered mRNA ribonucleoprotein complex components that assemble on mRNAs bound by multiple, distinct RBPs compared to those recruited by individual RBPs. This review builds upon our knowledge of combinatorial control of mRNA translation during the maturation of oocytes from Xenopus laevis, to address molecular strategies that may mediate RBP diplomacy and conflict resolution for coordinated control of mRNA translational output. Continued study of regulated ribonucleoprotein complex dynamics promises valuable new insights into mRNA translational control and may suggest novel therapeutic strategies for the treatment of disease.

Currently, there is very little information available regarding the microbiome associated with the wine production chain. Here, we used an amplicon sequencing approach based on high-throughput sequencing (HTS) to obtain a comprehensive assessment of the bacterial community associated with the production of three Apulian red wines, from grape to final product. The relationships among grape variety, the microbial community, and fermentation was investigated. Moreover, the winery microbiota was evaluated compared to the autochthonous species in vineyards that persist until the end of the winemaking process. The analysis highlighted the remarkable dynamics within the microbial communities during fermentation. A common microbial core shared among the examined wine varieties was observed, and the unique taxonomic signature of each wine appellation was revealed. New species belonging to the genus Halomonas were also reported. This study demonstrates the potential of this metagenomic approach, supported by optimized protocols, for identifying the biodiversity of the wine supply chain. The developed experimental pipeline offers new prospects for other research fields in which a comprehensive view of microbial community complexity and dynamics is desirable.

Lactobacillus rossiae is an obligately hetero-fermentative lactic acid bacterium, which can be isolated from a broad range of environments including sourdoughs, vegetables, fermented meat and flour, as well as the gastrointestinal tract of both humans and animals. In order to unravel distinctive genomic features of this particular species and investigate the phylogenetic positioning within the genus Lactobacillus, comparative genomics and phylogenomic approaches, followed by functional analyses were performed on L. rossiae DSM 15814T, showing how this type strain not only occupies an independent phylogenetic branch, but also possesses genomic features underscoring its biotechnological potential. This strain in fact represents one of a small number of bacteria known to encode a complete de novo biosynthetic pathway of vitamin B12 (in addition to other B vitamins such as folate and riboflavin). In addition, it possesses the capacity to utilize an extensive set of carbon sources, a characteristic that may contribute to environmental adaptation, perhaps enabling the strain's ability to populate different niches.

Microbiome research has grown substantially over the past decade in terms of the range of biomes sampled, identified taxa, and the volume of data derived from the samples. In particular, experimental approaches such as metagenomics, metabarcoding, metatranscriptomics and metaproteomics have provided profound insights into the vast, hitherto unknown, microbial biodiversity. The ELIXIR Marine Metagenomics Community, initiated amongst researchers focusing on marine microbiomes, has concentrated on promoting standards around microbiome-derived sequence analysis, as well as understanding the gaps in methods and reference databases, and solutions to computational overheads of performing such analyses. Nevertheless, the methods used and the challenges faced are not confined to marine studies, but are broadly applicable to all other biomes. Thus, expanding this Community to a more inclusive ELIXIR Microbiome Community will enable it to encompass a broad range of biomes and link expertise across ‘omics technologies. Furthermore, engaging with a large number of researchers will improve the efficiency and sustainability of bioinformatics infrastructure and resources for microbiome research (standards, data, tools, workflows, training), which will enable a deeper understanding of the function and taxonomic composition of the different microbial communities.