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Abstract Background In recent years, there has been a rapid increase in the number of microbial genomes reconstructed through shotgun sequencing, and obtained by newly developed approaches including metagenomic binning and single-cell sequencing. However, our ability to functionally characterize these genomes by experimental assays is orders of magnitude less efficient. Consequently, there is a pressing need for the development of swift and automated strategies for the functional classification of microbial genomes. Results The present work leverages a suite of supervised machine learning algorithms to establish a range of 86 metabolic and other ecological functions, such as methanotrophy and plastic degradation, starting from widely obtainable microbial genome annotations. Tests performed on independent datasets demonstrated robust performance across complete, fragmented, and incomplete genomes above a 70% completeness level for most of the considered functions. Application of the algorithms to the Biogas Microbiome database yielded predictions broadly consistent with current biological knowledge and correctly detecting functionally-related nuances of archaeal genomes. Finally, a case study focused on acetoclastic methanogenesis demonstrated how the developed machine learning models can be refined or expanded with models describing novel functions of interest. Conclusions The resulting tool, MICROPHERRET, incorporates a total of 86 models, one for each tested functional class, and can be applied to high-quality microbial genomes as well as to low-quality genomes derived from metagenomics and single-cell sequencing. MICROPHERRET can thus aid in understanding the functional role of newly generated genomes within their micro-ecological context.

Abstract Background Microbial biopolymers such as poly-3-hydroxybutyrate (PHB) are emerging as promising alternatives for sustainable production of biodegradable bioplastics. Their promise is heightened by the potential utilisation of photosynthetic organisms, thus exploiting sunlight and carbon dioxide as source of energy and carbon, respectively. The cyanobacterium Synechocystis sp. B12 is an attractive candidate for its superior ability to accumulate high amounts of PHB as well as for its high-light tolerance, which makes it extremely suitable for large-scale cultivation. Beyond its practical applications, B12 serves as an intriguing model for unravelling the molecular mechanisms behind PHB accumulation. Results Through a multifaceted approach, integrating physiological, genomic and transcriptomic analyses, this work identified genes involved in the upregulation of chlorophyll biosynthesis and phycobilisome degradation as the possible candidates providing Synechocystis sp. B12 an advantage in growth under high-light conditions. Gene expression differences in pentose phosphate pathway and acetyl-CoA metabolism were instead recognised as mainly responsible for the increased Synechocystis sp. B12 PHB production during nitrogen starvation. In both response to strong illumination and PHB accumulation, Synechocystis sp. B12 showed a metabolic modulation similar but more pronounced than the reference strain, yielding in better performances. Conclusions Our findings shed light on the molecular mechanisms of PHB biosynthesis, providing valuable insights for optimising the use of Synechocystis in economically viable and sustainable PHB production. In addition, this work supplies crucial knowledge about the metabolic processes involved in production and accumulation of these molecules, which can be seminal for the application to other microorganisms as well.

Bioactive peptides are short amino acid chains possessing biological activity and exerting physiological effects relevant to human health. Despite their therapeutic value, their identification remains a major problem, as it mainly relies on time-consuming in vitro tests. While bioinformatic tools for the identification of bioactive peptides are available, they are focused on specific functional classes and have not been systematically tested on realistic settings. To tackle this problem, bioactive peptide sequences and functions were here gathered from a variety of databases to generate a unified collection of bioactive peptides from microbial fermentation. This collection was organized into nine functional classes including some previously studied and some unexplored such as immunomodulatory, opioid and cardiovascular peptides. Upon assessing their sequence properties, four alternative encoding methods were tested in combination with a multitude of machine learning algorithms, from basic classifiers like logistic regression to advanced algorithms like BERT. Tests on a total of 171 models showed that, while some functions are intrinsically easier to detect, no single combination of classifiers and encoders worked universally well for all classes. For this reason, we unified all the best individual models for each class and generated CICERON (Classification of bIoaCtive pEptides fRom micrObial fermeNtation), a classification tool for the functional classification of peptides. State-of-the-art classifiers were found to underperform on our realistic benchmark dataset compared to the models included in CICERON. Altogether, our work provides a tool for real-world peptide classification and can serve as a benchmark for future model development.

Abstract Background The anaerobic digestion process degrades organic matter into simpler compounds and occurs in strictly anaerobic and microaerophilic environments. The process is carried out by a diverse community of microorganisms where each species has a unique role and it has relevant biotechnological applications since it is used for biogas production. Some aspects of the microbiome, including its interaction with phages, remains still unclear: a better comprehension of the community composition and role of each species is crucial for a cured understanding of the carbon cycle in anaerobic systems and improving biogas production. Results The primary objective of this study was to expand our understanding on the anaerobic digestion microbiome by jointly analyzing its prokaryotic and viral components. By integrating 192 additional datasets into a previous metagenomic database, the binning process generated 11,831 metagenome-assembled genomes from 314 metagenome samples published between 2014 and 2022, belonging to 4,568 non-redundant species based on ANI calculation and quality verification. CRISPR analysis on these genomes identified 76 archaeal genomes with active phage interactions. Moreover, single-nucleotide variants further pointed to archaea as the most critical members of the community. Among the MAGs, two methanogenic archaea, Methanothrix sp. 43zhSC_152 and Methanoculleus sp. 52maCN_3230, had the highest number of SNVs, with the latter having almost double the density of most other MAGs. Conclusions This study offers a more comprehensive understanding of microbial community structures that thrive at different temperatures. The findings revealed that the fraction of archaeal species characterized at the genome level and reported in public databases is higher than that of bacteria, although still quite limited. The identification of shared spacers between phages and microbes implies a history of phage-bacterial interactions, and specifically lysogenic infections. A significant number of SNVs were identified, primarily comprising synonymous and nonsynonymous variants. Together, the findings indicate that methanogenic archaea are subject to intense selective pressure and suggest that genomic variants play a critical role in the anaerobic digestion process. Overall, this study provides a more balanced and diverse representation of the anaerobic digestion microbiota in terms of geographic location, temperature range and feedstock utilization.

The production of biopeptides from food waste through microbial fermentation faces challenges arising from the diverse proteolytic abilities of microorganisms and substrate variability, impacting both the quality and yield of generated biopeptides. To address these challenges, preliminary in-silico bioinformatics analyses play a crucial role in evaluating suitable substrates and proteases for the fermentation process. However, existing tools lack comprehensive predictive capabilities for relevant proteases, substrate performance assessment, and final biopeptide family characterization. To overcome these limitations, we developed FEEDS (Food wastE biopEptiDe claSsifier), a novel biopeptide prediction and classification tool. FEEDS predicts biopeptide families based on microbial genome protease profiles and substrate composition during proteolysis. The tool also employs a machine learning approach for functional biopeptide classification. Results from testing on 1000 microbial genomes demonstrate the effectiveness of biopeptide classification, particularly in categorizing peptides derived from substrates like Hordeum vulgare and Vitis vinifera seed storage proteins. In addition to biopeptide classification, our study delves into the distinctive protease profiles of bacteria and yeast genomes. Bacterial genomes exhibited 60 to 100 proteases across 40–55 families. Contrastingly, yeast genomes displayed a more evenly distributed pattern with 150 to 160 protease-encoding genes across 60 to 67 families, surpassing bacterial counts. Remarkably, a substantial portion of yeast proteases (∼66 %) was secreted. Moreover, our integration of a machine learning methodology within the FEEDS pipeline proved highly effective, achieving over 80 % accuracy in predicting the function of peptides derived from seed storage proteins. Notably, longer peptide sequences exceeding 20 amino acids consistently displayed a higher probability of correct assignment compared to shorter counterparts.

IntroductionCyanobacteria appeared in the anoxic Archean Earth, evolving for the first time oxygenic photosynthesis and deeply changing the atmosphere by introducing oxygen. Starting possibly from UV-protected environments, characterized by low visible and far-red enriched light spectra, cyanobacteria spread everywhere on Earth thanks to their adaptation capabilities in light harvesting. In the last decade, few cyanobacteria species which can acclimate to far-red light through Far-Red Light Photoacclimation (FaRLiP) have been isolated. FaRLiP cyanobacteria were thus proposed as model organisms to study the origin of oxygenic photosynthesis as well as its possible functionality around stars with high far-red emission, the M-dwarfs. These stars are astrobiological targets, as their longevity could sustain life evolution and they demonstrated to host rocky terrestrial-like exoplanets within their Habitable Zone.MethodsWe studied the acclimation responses of the FaRLiP strain Chlorogloeopsis fritschii sp. PCC6912 and the non-FaRLiP strain Synechocystis sp. PCC6803 to the combination of three simulated light spectra (M-dwarf, solar and far-red) and two atmospheric compositions (oxic, anoxic). We first checked their growth, O2 production and pigment composition, then we studied their transcriptional responses by RNA sequencing under each combination of light spectrum and atmosphere conditions.Results and discussionPCC6803 did not show relevant differences in gene expression when comparing the responses to M-dwarf and solar-simulated lights, while far-red caused a variation in the transcriptional level of many genes. PCC6912 showed, on the contrary, different transcriptional responses to each light condition and activated the FaRLiP response under the M-dwarf simulated light. Surprisingly, the anoxic atmosphere did not impact the transcriptional profile of the 2 strains significantly. Results show that both cyanobacteria seem inherently prepared for anoxia and to harvest the photons emitted by a simulated M-dwarf star, whether they are only visible (PCC6803) or also far-red photons (PCC6912). They also show that visible photons in the simulated M-dwarf are sufficient to keep a similar metabolism with respect to solar-simulated light.ConclusionResults prove the adaptability of the cyanobacterial metabolism and enhance the plausibility of finding oxygenic biospheres on exoplanets orbiting M-dwarf stars.

ABSTRACTWe report the first use of constraint-based microbial community modeling on a single individual with episodic inflammation of the gastrointestinal tract, who has a well documented set of colonic inflammatory biomarkers, as well as metagenomically-sequenced fecal time series covering seven dates over 16 months. Between the first two time steps the individual was treated with both steroids and antibiotics. Our methodology enabled us to identify numerous time-correlated microbial species and metabolites. We found that the individual’s dynamical microbial ecology in the disease state led to time-varying in silico overproduction, compared to healthy controls, of more than 24 biologically important metabolites, including methane, thiamine, formaldehyde, trimethylamine N-oxide, folic acid, serotonin, histamine, and tryptamine. The microbe-metabolite contribution analysis revealed that some Dialister species changed metabolic pathways according to the inflammation phases. At the first time point, characterized by the highest levels of serum (complex reactive protein) and fecal (calprotectin) inflammation biomarkers, they produced L-serine or formate. The production of the compounds, through a cascade effect, was mediated by the interaction with pathogenic Escherichia coli strains and Desulfovibrio piger. We integrated the microbial community metabolic models of each time point with a male whole-body, organ-resolved model of human metabolism to track the metabolic consequences of dysbiosis at different body sites. The presence of D. piger in the gut microbiome influenced the sulfur metabolism with a domino effect affecting the liver. These results revealed large longitudinal variations in an individual’s gut microbiome ecology and metabolite production, potentially impacting other organs in the body. Future simulations with more time points from an individual could permit us to assess how external drivers, such as diet change or medical interventions, drive microbial community dynamics.

Abstract Background Carbon fixation through biological methanation has emerged as a promising technology to produce renewable energy in the context of the circular economy. The anaerobic digestion microbiome is the fundamental biological system operating biogas upgrading and is paramount in power-to-gas conversion. Carbon dioxide (CO2) methanation is frequently performed by microbiota attached to solid supports generating biofilms. Despite the apparent simplicity of the microbial community involved in biogas upgrading, the dynamics behind most of the interspecies interaction remain obscure. To understand the role of the microbial species in CO2 fixation, the biofilm generated during the biogas upgrading process has been selected as a case study. The present work investigates via genome-centric metagenomics, based on a hybrid Nanopore-Illumina approach the biofilm developed on the diffusion devices of four ex situ biogas upgrading reactors. Moreover, genome-guided metabolic reconstruction and flux balance analysis were used to propose a biological role for the dominant microbes. Results The combined microbiome was composed of 59 species, with five being dominant (> 70% of total abundance); the metagenome-assembled genomes representing these species were refined to reach a high level of completeness. Genome-guided metabolic analysis appointed Firmicutes sp. GSMM966 as the main responsible for biofilm formation. Additionally, species interactions were investigated considering their co-occurrence in 134 samples, and in terms of metabolic exchanges through flux balance simulation in a simplified medium. Some of the most abundant species (e.g., Limnochordia sp. GSMM975) were widespread (~ 67% of tested experiments), while others (e.g., Methanothermobacter wolfeii GSMM957) had a scattered distribution. Genome-scale metabolic models of the microbial community were built with boundary conditions taken from the biochemical data and showed the presence of a flexible interaction network mainly based on hydrogen and carbon dioxide uptake and formate exchange. Conclusions Our work investigated the interplay between five dominant species within the biofilm and showed their importance in a large spectrum of anaerobic biogas reactor samples. Flux balance analysis provided a deeper insight into the potential syntrophic interaction between species, especially Limnochordia sp. GSMM975 and Methanothermobacter wolfeii GSMM957. Finally, it suggested species interactions to be based on formate and amino acids exchanges. Video Abstract

Abstract Background The viral community has the potential to influence the structure of the microbiome and thus the yield of the anaerobic digestion process. However, the virome composition in anaerobic digestion is still under-investigated. A viral induction experiment was conducted on separate batches undergoing a series of DNA-damaging stresses, in order to coerce temperate viruses to enter the lytic cycle. Results The sequencing of the metagenome revealed a viral community almost entirely composed of tailed bacteriophages of the order Caudovirales. Following a binning procedure 1,092 viral and 120 prokaryotic genomes were reconstructed, 64 of which included an integrated prophage in their sequence. Clustering of coverage profiles revealed the presence of species, both viral and microbial, sharing similar reactions to shocks. A group of viral genomes, which increase under organic overload and decrease under basic pH, uniquely encode the yopX gene, which is involved in the induction of temperate prophages. Moreover, the in-silico functional analysis revealed an enrichment of sialidases in viral genomes. These genes are associated with tail proteins and, as such, are hypothesised to be involved in the interaction with the host. Archaea registered the most pronounced changes in relation to shocks and featured behaviours not shared with other species. Subsequently, data from 123 different samples of the global anaerobic digestion database was used to determine coverage profiles of host and viral genomes on a broader scale. Conclusions Viruses are key components in anaerobic digestion environments, shaping the microbial guilds which drive the methanogenesis process. In turn, environmental conditions are pivotal in shaping the viral community and the rate of induction of temperate viruses. This study provides an initial insight into the complexity of the anaerobic digestion virome and its relation with the microbial community and the diverse environmental parameters. Video Abstract

Background: The rapid accumulation of sequencing data from metagenomic studies is enabling the generation of huge collections of microbial genomes, with new challenges for mapping their functional potential. In particular, metagenome-assembled genomes are typically incomplete and harbor partial gene sequences that can limit their annotation from traditional tools. New scalable solutions are thus needed to facilitate the evaluation of functional potential in microbial genomes. Methods: To resolve annotation gaps in microbial genomes, we developed KEMET, an open-source Python library devised for the analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG) functional units. KEMET focuses on the in-depth analysis of metabolic reaction networks to identify missing orthologs through hidden Markov model profiles. Results: We evaluate the potential of KEMET for expanding functional annotations by simulating the effect of assembly issues on real gene sequences and showing that our approach can identify missing KEGG orthologs. Additionally, we show that recovered gene annotations can sensibly increase the quality of draft genome-scale metabolic models obtained from metagenome-assembled genomes, in some cases reaching the accuracy of models generated from complete genomes. Conclusions: KEMET therefore allows expanding genome annotations by targeted searches for orthologous sequences, enabling a better qualitative and quantitative assessment of metabolic capabilities in novel microbial organisms.

The knowledge of the microbiome in the anaerobic digestion (AD) is critical for stabilizing the process and optimizing the biogas yield. This work investigates the microbial ecology in four full-scale biogas plants with different feedstocks and process parameters. The three agricultural plants sharing similar feedstocks’ composition (mostly rich in proteins, cellulose and hemicellulose), have several hydrolytic and methanogenic species in common, suggesting that their substrates specifically shape the microbiomes. Particularly, the hydrolytic and likely syntrophic Defluviitoga tunisiensis was detected as the most abundant species in one reactor, representing 21.2% of the community. On the other hand, the biogas plant treating the organic fraction of municipal solid waste (OFMSW), whose composition was much higher in hash and lower in proteins, displayed a quite different microbiome with a much lower abundance of Bacteroidales sp. much higher of Clostridiaceae. Moreover, this AD was clearly influenced by COVID-19 restrictions as both substrate availability and composition suddenly changed causing the wash-out of most bacterial and methanogenic species and leading to a deep modification of the microbial structure. The abundance of Methanosarcina flavescens greatly increased up to 36.5% of the total operational taxonomic units (OTUs), suggesting a switch from the hydrogenotrophic to the acetoclastic methanogenic pathway. This is the first report on the COVID-19 impact on the AD microbiome of a full-scale anaerobic digestor. Moreover, this paper demonstrated that the feedstock composition can differentially shape both bacterial and archaeal strains of the AD process.

ABSTRACT This study provided a new perspective on the bacterial community succession during sauerkraut fermentation, and on resulting metabolic functions. While culture-dependent methods confirmed the key role of the well-known core microbiome species, metagenomic approach (shotgun) revealed Secundilactobacillus malefermentans as a species of the core microbiome, especially during the last weeks of fermentation. Although the potentiality of S. malefermentans has not yet fully explored, it held core functional genes usually attributed to others lactic acid bacteria driving sauerkraut fermentation. Based on our results it is arguable that S. malefermentans might have a key a role during sauerkraut fermentation carried out at low temperature. Under our experimental conditions, the profile of phenolic compounds changed throughout sauerkraut fermentation. The amount of free phenolics, including free phenolic acids, increased at the beginning of the fermentation, whereas the conversion of phenolic acids into microbial derivatives was consistent during the last part of the sauerkraut fermentation. We pioneered correlating changes in the phenolics profile to changes in the microbiome, although the framework presented is still fragmentary. Annotated genes linked to the phenolic compounds metabolism (VprA and padA) were found in many core species during the whole process. A high metabolic potential for phenolics bioconversion emerged for lactobacilli and Pediococcus spp. through correlation analysis between microbiome composition and phenolics profile. IMPORTANCE Our study was not limited to describe the succession pattern of the microbial community during sauerkraut fermentation, but also revealed how some neglected bacterial players belong to the core species during sauerkrauts processing, especially at low temperature. Such species might have a role as potential starters to optimize the fermentation processes and to obtain sauerkrauts with improved and standardized nutritional and sensory features. Furthermore, our correlations between microbiome composition and phenolics profile might also represent new references for sauerkraut biotechnology, aiming to identify new metabolic drivers of potential sauerkraut functionalities. Finally, sauerkraut ecosystem is a tractable model, although with high level of complexity, and resultant ecological information might be extended to other plant ecosystems.

Abstract Background During the acetogenic step of anaerobic digestion, the products of acidogenesis are oxidized to substrates for methanogenesis: hydrogen, carbon dioxide and acetate. Acetogenesis and methanogenesis are highly interconnected processes due to the syntrophic associations between acetogenic bacteria and hydrogenotrophic methanogens, allowing the whole process to become thermodynamically favorable. The aim of this study is to determine the influence of the dominant acidic products on the metabolic pathways of methane formation and to find a core microbiome and substrate-specific species in a mixed biogas-producing system. Results Four methane-producing microbial communities were fed with artificial media having one dominant component, respectively, lactate, butyrate, propionate and acetate, for 896 days in 3.5-L Up-flow Anaerobic Sludge Blanket (UASB) bioreactors. All the microbial communities showed moderately different methane production and utilization of the substrates. Analyses of stable carbon isotope composition of the fermentation gas and the substrates showed differences in average values of δ13C(CH4) and δ13C(CO2) revealing that acetate and lactate strongly favored the acetotrophic pathway, while butyrate and propionate favored the hydrogenotrophic pathway of methane formation. Genome-centric metagenomic analysis recovered 234 Metagenome Assembled Genomes (MAGs), including 31 archaeal and 203 bacterial species, mostly unknown and uncultivable. MAGs accounted for 54%–67% of the entire microbial community (depending on the bioreactor) and evidenced that the microbiome is extremely complex in terms of the number of species. The core microbiome was composed of Methanothrix soehngenii (the most abundant), Methanoculleus sp., unknown Bacteroidales and Spirochaetaceae. Relative abundance analysis of all the samples revealed microbes having substrate preferences. Substrate-specific species were mostly unknown and not predominant in the microbial communities. Conclusions In this experimental system, the dominant fermentation products subjected to methanogenesis moderately modified the final effect of bioreactor performance. At the molecular level, a different contribution of acetotrophic and hydrogenotrophic pathways for methane production, a very high level of new species recovered, and a moderate variability in microbial composition depending on substrate availability were evidenced. Propionate was not a factor ceasing methane production. All these findings are relevant because lactate, acetate, propionate and butyrate are the universal products of acidogenesis, regardless of feedstock.

Natural yeast with superior fermentative traits can serve as a platform for the development of recombinant strains that can be used to improve the sustainability of bioethanol production from starch. This process will benefit from a consolidated bioprocessing (CBP) approach where an engineered strain producing amylases directly converts starch into ethanol. The yeast Saccharomyces cerevisiae L20, previously selected as outperforming the benchmark yeast Ethanol Red, was here subjected to a comparative genomic investigation using a dataset of industrial S. cerevisiae strains. Along with Ethanol Red, strain L20 was then engineered for the expression of α-amylase amyA and glucoamylase glaA genes from Aspergillus tubingensis by employing two different approaches (delta integration and CRISPR/Cas9). A correlation between the number of integrated copies and the hydrolytic abilities of the recombinants was investigated. L20 demonstrated important traits for the construction of a proficient CBP yeast. Despite showing a close relatedness to commercial wine yeast and the benchmark Ethanol Red, a unique profile of gene copy number variations (CNVs) was found in L20, mainly encoding membrane transporters and secretion pathway proteins but also the fermentative metabolism. Moreover, the genome annotation disclosed seven open reading frames (ORFs) in L20 that are absent in the reference S288C genome. Genome engineering was successfully implemented for amylase production. However, with equal amylase gene copies, L20 proved its proficiency as a good enzyme secretor by exhibiting a markedly higher amylolytic activity than Ethanol Red, in compliance to the findings of the genomic exploration. The recombinant L20 dT8 exhibited the highest amylolytic activity and produced more than 4 g/L of ethanol from 2% starch in a CBP setting without the addition of supplementary enzymes. Based on the performance of this strain, an amylase/glucoamylase ratio of 1:2.5 was suggested as baseline for further improvement of the CBP ability. Overall, L20 showed important traits for the future construction of a proficient CBP yeast. As such, this work shows that natural S. cerevisiae strains can be used for the expression of foreign secreted enzymes, paving the way to strain improvement for the starch-to-bioethanol route.

Abstract Methanogenesis, a biological process mediated by complex microbial communities, has attracted great attention due to its contribution to global warming and potential in biotechnological applications. The current study unveiled the core microbial methanogenic metabolisms in anaerobic vessel ecosystems by applying combined genome-centric metagenomics and metatranscriptomics. Here, we demonstrate that an enriched natural system, fueled only with acetate, could support a bacteria-dominated microbiota employing a multi-trophic methanogenic process. Moreover, significant changes, in terms of microbial structure and function, were recorded after the system was supplemented with additional H2. Methanosarcina thermophila, the predominant methanogen prior to H2 addition, simultaneously performed acetoclastic, hydrogenotrophic, and methylotrophic methanogenesis. The methanogenic pattern changed after the addition of H2, which immediately stimulated Methanomicrobia-activity and was followed by a slow enrichment of Methanobacteria members. Interestingly, the essential genes involved in the Wood-Ljungdahl pathway were not expressed in bacterial members. The high expression of a glycine cleavage system indicated the activation of alternative metabolic pathways for acetate metabolism, which were reconstructed in the most abundant bacterial genomes. Moreover, as evidenced by predicted auxotrophies, we propose that specific microbes of the community were forming symbiotic relationships, thus reducing the biosynthetic burden of individual members. These results provide new information that will facilitate future microbial ecology studies of interspecies competition and symbiosis in methanogenic niches. Video abstract.

Abstract Background Microorganisms in biogas reactors are essential for degradation of organic matter and methane production. However, a comprehensive genome-centric comparison, including relevant metadata for each sample, is still needed to identify the globally distributed biogas community members and serve as a reliable repository. Results Here, 134 publicly available metagenomes derived from different biogas reactors were used to recover 1635 metagenome-assembled genomes (MAGs) representing different biogas bacterial and archaeal species. All genomes were estimated to be > 50% complete and nearly half ≥ 90% complete with ≤ 5% contamination. In most samples, specialized microbial communities were established, while only a few taxa were widespread among the different reactor systems. Metabolic reconstruction of the MAGs enabled the prediction of functional traits related to biomass degradation and methane production from waste biomass. An extensive evaluation of the replication index provided an estimation of the growth dynamics for microbes involved in different steps of the food chain. Conclusions The outcome of this study highlights a high flexibility of the biogas microbiome, allowing it to modify its composition and to adapt to the environmental conditions, including temperatures and a wide range of substrates. Our findings enhance our mechanistic understanding of the AD microbiome and substantially extend the existing repository of genomes. The established database represents a relevant resource for future studies related to this engineered ecosystem.

Here the draft genome sequence of Lactobacillus paracasei strain DTA83, isolated from stools of healthy infants in Rio de Janeiro (Brazil), is reported. The 2.8-Mb genome possesses 2825 protein-coding sequences distributed on 330 SEED subsystems. This strain belongs to a set of potentially probiotic Lactobacillus spp. strains used to study genetic factors related to antibiotic resistance after stress conditions, such as simulated gastrointestinal conditions. The complete genome data have been deposited in GenBank under the accession number QRBH00000000, https://www.ncbi.nlm.nih.gov/nuccore/ QRBH00000000.

Abstract Background The expansion of renewable energy produced by windmills and photovoltaic panels has generated a considerable electricity surplus, which can be utilized in water electrolysis systems for hydrogen production. The resulting hydrogen can then be funneled to anaerobic digesters for biogas upgrading (biomethanation) purposes (power-to-methane) or to produce high value-added compounds such as short-chain fatty acids (power-to-chemicals). Genome-centric metagenomics and metatranscriptomic analyses were performed to better understand the metabolic dynamics associated with H2 injection in two different configurations of anaerobic digesters treating acidic wastes, specifically cheese manufacturing byproducts. These approaches revealed the key-genes involved in methanation and carbon fixation pathways at species level. Results The biogas upgrading process in the single-stage configuration increased the CH4 content by 7%. The dominant methanogenic species responsible for the upregulation of the hydrogenotrophic pathway in this reactor was Methanothermobacter wolfeii UC0008. In the two-stage configuration, H2 injection induced an upregulation of CO2 fixation pathways producing short-chain fatty acids, mainly acetate and butyrate. In this configuration, the abundant species Anaerobaculum hydrogeniformans UC0046 and Defluviitoga tunisiensis UC0050 primarily upregulated genes related to electron transport chains, suggesting putative syntrophisms with hydrogen scavenger microbes. Interestingly, Tepidanaerobacter acetatoxydans UC0018 did not act as an acetate-oxidizer in either reactor configurations, and instead regulated pathways involved in acetate production and uptake. A putative syntrophic association between Coprothermobacter proteolyticus UC0011 and M. wolfeii UC0008 was proposed in the two-stage reactor. In order to support the transcriptomic findings regarding the hydrogen utilization routes, an advanced bioconversion model was adapted for the simulation of the single- and two-stage reactor setups. Conclusions This is the first study investigating biogas reactor metatranscriptome dynamics following hydrogen injection for biomethanation and carbon fixation to short-chain fatty acids purposes. The same microbes showed different patterns of metabolic regulation in the two reactor configurations. It was observed an effect of the specialized acidogenic reactor on the overall microbial consortium composition and activity in the two-stage digester. There were also suggested the main species responsible for methanation, short-chain fatty acids production, and electron transport chain mechanisms, in both reactor configurations.

Glutathione (GSH) is an antioxidant molecule of great technological interest due to its wide range of applications in the food and beverage industry. In winemaking, although glutathione is produced during fermentation, its addition is possible for the control of oxidative spoilage of wine. Recently, to improve wine quality, mixed fermentation has been proposed by introducing a selection of non-Saccharomyces yeasts as complementary starters to the oenological species S. cerevisiae. Among them, Starmerella bacillaris, an osmophilic and high glycerol producer yeast, has been extensively studied. In the present study, the genomes of two S. bacillaris strains were compared with S. cerevisiae to identify the GSH metabolic pathway. The results showed that GSH biosynthesis includes the GSH1 and GSH2 genes in both species. The identification of a new transcription factor which binds sites in the promoter region of these genes underlined differences in the transcriptional regulation of both species. Additionally, between S. bacillaris strains, a high number of polymorphisms was found in genes involved in GSH redox balance. Preliminary laboratory scale fermentations revealed marked differences in the cell glutathione content of the two S. bacillaris strains. By comparing genomes, it was possible to gain a better understanding of the genes involved in the GSH metabolism pathway in S. bacillaris.

Reducing CO2 emissions is necessary to alleviate rising global temperature. Renewable sources of energy are becoming an increasingly important substitute for fossil fuels. An important step in this direction is the isolation of novel, technologically relevant microorganisms. Nitratireductor sp. strain OM-1 can convert volatile short-chain fatty acids in wastewater into 2-butenoic acid and its ester and can accumulate intracellularly esterified compounds up to 50% of its dried cell weight under nitrogen-depleted conditions. It is believed that a novel fatty acid biosynthesis pathway including an esterifying enzyme is encoded in its genome. In this study, we report the whole-genome sequence (4.8 Mb) of OM-1, which comprises a chromosome (3,977,827 bp) and a megaplasmid (857,937 bp). This sequence information provides insight into the genome organization and biochemical pathways of OM-1. In addition, we identified lipid biosynthesis pathways in OM-1, paving the way to a better understanding of its biochemical characterization. Keywords: Nitratireductor, Biodiesel production, Short-chain fatty acid, Ester synthesis, Whole genome sequence

In the lignocellulosic yeast development, metabolic burden relates to redirection of resources from regular cellular activities toward the needs created by recombinant protein production. As a result, growth parameters may be greatly affected. Noteworthy, Saccharomyces cerevisiae M2n[pBKD2-Pccbgl1]-C1, previously developed by multiple δ-integration of the β-glucosidase BGL3, did not show any detectable metabolic burden. This work aims to test the hypothesis that the metabolic burden and the metabolomic perturbation induced by the δ-integration of a yeast strain, could differ significantly. The engineered strain was evaluated in terms of metabolic performances and metabolomic alterations in different conditions typical of the bioethanol industry. Results indicate that the multiple δ-integration did not affect the ability of the engineered strain to grow on different carbon sources and to tolerate increasing concentrations of ethanol and inhibitory compounds. Conversely, metabolomic profiles were significantly altered both under growing and stressing conditions, indicating a large extent of metabolic reshuffling involved in the maintenance of the metabolic homeostasis. Considering that four copies of BGL3 gene have been integrated without affecting any parental genes or promoter sequences, deeper studies are needed to unveil the mechanisms implied in these metabolomic changes, thus supporting the optimization of protein production in engineered strains.

Abstract Bovine mastitis remains the main cause of economic losses for dairy farmers. Mammary pathogenic Escherichia coli (MPEC) is related to an acute mastitis and its treatment is still based on the use of antibiotics. In the era of antimicrobial resistance (AMR), bacterial viruses (bacteriophages) present as an efficient treatment or prophylactic option. However, this makes it essential that its genetic structure, stability and interaction with the host immune system be thoroughly characterized. The present study analyzed a novel, broad host-range anti-mastitis agent, the T4virus vB_EcoM-UFV13 in genomic terms, and its activity against a MPEC strain in an experimental E. coli-induced mastitis mouse model. 4,975 Single Nucleotide Polymorphisms (SNPs) were assigned between vB_EcoM-UFV13 and E. coli phage T4 genomes with high impact on coding sequences (CDS) (37.60%) for virion proteins. Phylogenetic trees and genome analysis supported a recent infection mix between vB_EcoM-UFV13 and Shigella phage Shfl2. After a viral stability evaluation (e.g pH and temperature), intramammary administration (MOI 10) resulted in a 10-fold reduction in bacterial load. Furthermore, pro-inflammatory cytokines, such as IL-6 and TNF-α, were observed after viral treatment. This work brings the whole characterization and immune response to vB_EcoM-UFV13, a biocontrol candidate for bovine mastitis.

Lactobacillus helveticus belongs to the large group of lactic acid bacteria (LAB), which are the major players in the fermentation of a wide range of foods. LAB are also present in the human gut, which has often been exploited as a reservoir of potential novel probiotic strains, but several parameters need to be assessed before establishing their safety and potential use for human consumption. In the present study, six L. helveticus strains isolated from natural whey cultures were analyzed for their phenotype and genotype in exopolysaccharide (EPS) production, low pH and bile salt tolerance, bile salt hydrolase (BSH) activity, and antibiotic resistance profile. In addition, a comparative genomic investigation was performed between the six newly sequenced strains and the 51 publicly available genomes of L. helveticus to define the pangenome structure. The results indicate that the newly sequenced strain UC1267 and the deposited strain DSM 20075 can be considered good candidates for gut-adapted strains due to their ability to survive in the presence of 0.2% glycocholic acid (GCA) and 1% taurocholic and taurodeoxycholic acid (TDCA). Moreover, these strains had the highest bile salt deconjugation activity among the tested L. helveticus strains. Considering the safety profile, none of these strains presented antibiotic resistance phenotypically and/or at the genome level. The pangenome analysis revealed genes specific to the new isolates, such as enzymes related to folate biosynthesis in strains UC1266 and UC1267 and an integrated phage in strain UC1035. Finally, the presence of maltose-degrading enzymes and multiple copies of 6-phospho-β-glucosidase genes in our strains indicates the capability to metabolize sugars other than lactose, which is related solely to dairy niches.

The Euganean Thermal District has been known since Roman times for the therapeutic properties of peloids, obtained from natural clays that have undergone a traditional maturation process. This leads to the growth of a green microbial biofilm with Cyanobacteria and the target species Phormidium sp. ETS-05 as fundamental components for their ability to synthetize anti-inflammatory molecules. Currently, in-depth studies on the microbiota colonizing Euganean peloids, as in general on peloids utilized worldwide, are missing. This is the first characterization of the microbial community of Euganean thermal muds, also investigating the effects of environmental factors on its composition. We analysed 53 muds from 29 sites (Spas) using a polyphasic approach, finding a stable microbiota peculiar to the area. Differences among mud samples mainly depended on two parameters: water temperature and shading of mud maturation plants. In the range 37–47 °C and in the case of irradiance attenuation due to the presence of protective roofs, a statistically significant higher mud Chl a content was detected. Moreover, in these conditions, a characteristic microbial and Cyanobacteria population composition dominated by Phormidium sp. ETS-05 was observed. We also obtained the complete genome sequence of this target species using a mixed sequencing approach based on Illumina and Nanopore sequencing.

crAss-like viruses are a putative family of bacteriophages recently discovered. The eponym of the clade, crAssphage, is an enteric bacteriophage estimated to be present in at least half of the human population and it constitutes up to 90% of the sequences in some human fecal viral metagenomic datasets. We focused on the evolutionary dynamics of the genes encoded on the crAssphage genome. By investigating the conservation of the genes, a consistent variation in the evolutionary rates across the different functional groups was found. Gene duplications in crAss-like genomes were detected. By exploring the differences among the functional categories of the genes, we confirmed that the genes encoding capsid proteins were the most ubiquitous, despite their overall low sequence conservation. It was possible to identify a core of proteins whose evolutionary trees strongly correlate with each other, suggesting their genetic interaction. This group includes the capsid proteins, which are thus established as extremely suitable for rebuilding the phylogenetic tree of this viral clade. A negative correlation between the ubiquity and the conservation of viral protein sequences was shown. Together, this study provides an in-depth picture of the evolution of different genes in crAss-like viruses.

During the development of the central nervous system, the proliferation of neural progenitors and differentiation of neurons and glia are tightly regulated by different transcription factors and signaling cascades, such as the Wnt and Shh pathways. This process takes place in cooperation with several microRNAs, some of which evolutionarily conserved in vertebrates, from teleosts to mammals. We focused our attention on miR-7, as its role in the regulation of cell signaling during neural development is still unclear. Specifically, we used human stem cell cultures and whole zebrafish embryos to study, in vitro and in vivo, the role of miR-7 in the development of dopaminergic (DA) neurons, a cell type primarily affected in Parkinson’s disease. We demonstrated that the zebrafish homologue of miR-7 (miR-7a) is expressed in the forebrain during the development of DA neurons. Moreover, we identified 143 target genes downregulated by miR-7, including the neural fate markers TCF4 and TCF12, as well as the Wnt pathway effector TCF7L2. We then demonstrated that miR-7 negatively regulates the proliferation of DA-progenitors by inhibiting Wnt/β-catenin signaling in zebrafish embryos. In parallel, miR-7 positively regulates Shh signaling, thus controlling the balance between oligodendroglial and DA neuronal cell fates. In summary, this study identifies a new molecular cross-talk between Wnt and Shh signaling pathways during the development of DA-neurons. Being mediated by a microRNA, this mechanism represents a promising target in cell differentiation therapies for Parkinson’s disease.

Streptococcus thermophilus is a species widely used in the dairy industry for its capability to rapidly ferment lactose and lower the pH. The capability to use galactose produced from lactose hydrolysis is strain dependent and most of commercial S. thermophilus strains are galactose-negative (Gal−), although galactose-positive (Gal+) would be more technologically advantageous because this feature could provide additional metabolic products and prevent galactose accumulation in foods. In this study, a next generation sequencing transcriptome approach was used to compare for the first time a Gal+ and a Gal− strain to characterize their whole metabolism and shed light on their different properties, metabolic performance and gene regulation. Transcriptome analysis revealed that all genes of the gal operon were expressed very differently in Gal+ and in the Gal− strains. The expression of several genes involved in mixed acid fermentation, PTS sugars transporter and stress response were found enhanced in Gal+. Conversely, genes related to amino acids, proteins metabolism and CRISPR associated proteins were under-expressed. In addition, the strains showed a diverse series of predicted genes controlled by the transcriptional factor catabolite control protein A (CcpA). Overall, transcriptomic analysis suggests that the Gal+ strain underwent a metabolic remodeling to cope with the changed environmental conditions.

Biogas upgrading via carbon dioxide hydrogenation is an emerging technology for electrofuel production. The biomethanation efficiency is strongly dependent on a balanced microbial consortium, whose high- resolution characterization along with their functional potential and interactions are pivotal for process optimization. The present work is the first genome-centric metagenomic study on mesophilic and thermophilic biogas upgrading reactors aiming to define the metabolic profile of more than 200 uncultivated microbes involved in hydrogen assisted methanogenesis. The outcomes from predictive functional analyses were correlated with microbial abundance variations to clarify the effect of process parameters on the community. The operational temperature significantly influenced the microbial richness of the reactors, while the H2 addition distinctively alternated the abundance of the taxa. Two different Methanoculleus species (one mesophilic and one thermophilic) were identified as the main responsible ones for methane metabolism. Finally, it was demonstrated that the addition of H2 exerted a selective pressure on the concerted or syntrophic interactions of specific microbes functionally related to carbon fixation, propionate and butanoate metabolisms. Novel bacteria were identified as candidate syntrophic acetate oxidizers (e.g., Tepidanaerobacter sp. DTU063), while the addition of H2 favored the proliferation of potential homoacetogens (e.g., Clostridia sp. DTU183). Population genomes encoding genes of Wood-Ljungdahl pathway were mainly thermophilic, while propionate degraders were mostly identified at mesophilic conditions. Finally, putative syntrophic interactions were identified between microbes that have either versatile metabolic abilities or are obligate/facultative syntrophs.

Streptococcus thermophilus is considered one of the most important species for the dairy industry. Due to their diffusion in dairy environments, bacteriophages can represent a threat to this widely used bacterial species. Despite the presence of a CRISPR-Cas system in the S. thermophilus genome, some lysogenic strains harbor cryptic prophages that can increase the phage-host resistance defense. This characteristic was identified in the dairy strain S. thermophilus M17PTZA496, which contains two integrated prophages 51.8 and 28.3 Kb long, respectively. In the present study, defense mechanisms, such as a lipoprotein-encoding gene and Siphovirus Gp157, the last associated to the presence of a noncoding viral DNA element, were identified in the prophage M17PTZA496 genome. The ability to overexpress genes involved in these defense mechanisms under specific stressful conditions, such as phage attack, has been demonstrated. Despite the addition of increasing amounts of Mitomycin C, M17PTZA496 was found to be non-inducible. However, the transcriptional activity of the phage terminase large subunit was detected in the presence of the antagonist phage vB_SthS-VA460 and of Mitomycin C. The discovery of an additional immune mechanism, associated with bacteriophage-insensitive strains, is of utmost importance, for technological applications and industrial processes. To our knowledge, this is the first study reporting the capability of a prophage integrated into the S. thermophilus genome expressing different phage defense mechanisms. Bacteriophages are widespread entities that constantly threaten starter cultures in the dairy industry. In cheese and yogurt manufacturing, the lysis of Streptococcus thermophilus cultures by viral attacks can lead to huge economic losses. Nowadays S. thermophilus is considered a well-stablished model organism for the study of natural adaptive immunity (CRISPR-Cas) against phage and plasmids, however, the identification of novel bacteriophage-resistance mechanisms, in this species, is strongly desirable. Here, we demonstrated that the presence of a non-inducible prophage confers phage-immunity to an S. thermophilus strain, by the presence of ltp and a viral noncoding region. S. thermophilus M17PTZA496 arises as an unconventional model to study phage resistance and potentially represents an alternative starter strain for dairy productions.

Alström Syndrome (ALMS) is a rare genetic disorder (483 living cases), characterized by many clinical manifestations, including blindness, obesity, type 2 diabetes and cardiomyopathy. ALMS is caused by mutations in the ALMS1 gene, encoding for a large protein with implicated roles in ciliary function, cellular quiescence and intracellular transport. Patients with ALMS have extensive fibrosis in nearly all tissues resulting in a progressive organ failure which is often the ultimate cause of death. To focus on the role of ALMS1 mutations in the generation and maintenance of this pathological fibrosis, we performed gene expression analysis, ultrastructural characterization and functional assays in 4 dermal fibroblast cultures from ALMS patients. Using a genome-wide gene expression analysis we found alterations in genes belonging to specific categories (cell cycle, extracellular matrix (ECM) and fibrosis, cellular architecture/motility and apoptosis). ALMS fibroblasts display cytoskeleton abnormalities and migration impairment, up-regulate the expression and production of collagens and despite the increase in the cell cycle length are more resistant to apoptosis. Therefore ALMS1-deficient fibroblasts showed a constitutively activated myofibroblast phenotype even if they do not derive from a fibrotic lesion. Our results support a genetic basis for the fibrosis observed in ALMS and show that both an excessive ECM production and a failure to eliminate myofibroblasts are key mechanisms. Furthermore, our findings suggest new roles for ALMS1 in both intra- and extra-cellular events which are essential not only for the normal cellular function but also for cell-cell and ECM-cell interactions.

Ankrd2 (also known as Arpp) together with Ankrd1/CARP and DARP are members of the MARP mechanosensing proteins that form a complex with titin (N2A)/calpain 3 protease/myopalladin. In muscle, Ankrd2 is located in the I-band of the sarcomere and moves to the nucleus of adjacent myofibers on muscle injury. In myoblasts it is predominantly in the nucleus and on differentiation shifts from the nucleus to the cytoplasm. In agreement with its role as a sensor it interacts both with sarcomeric proteins and transcription factors.Expression profiling of endogenous Ankrd2 silenced in human myotubes was undertaken to elucidate its role as an intermediary in cell signaling pathways. Silencing Ankrd2 expression altered the expression of genes involved in both intercellular communication (cytokine-cytokine receptor interaction, endocytosis, focal adhesion, tight junction, gap junction and regulation of the actin cytoskeleton) and intracellular communication (calcium, insulin, MAPK, p53, TGF-β and Wnt signaling). The significance of Ankrd2 in cell signaling was strengthened by the fact that we were able to show for the first time that Nkx2.5 and p53 are upstream effectors of the Ankrd2 gene and that Ankrd1/CARP, another MARP member, can modulate the transcriptional ability of MyoD on the Ankrd2 promoter. Another novel finding was the interaction between Ankrd2 and proteins with PDZ and SH3 domains, further supporting its role in signaling. It is noteworthy that we demonstrated that transcription factors PAX6, LHX2, NFIL3 and MECP2, were able to bind both the Ankrd2 protein and its promoter indicating the presence of a regulatory feedback loop mechanism.In conclusion we demonstrate that Ankrd2 is a potent regulator in muscle cells affecting a multitude of pathways and processes.