Functional prediction based on 16S rRNA metagenome data from bacterial microbiota associated with macroalgae from the Peruvian coast.

Macroalgae are vital reservoirs for essential epibiotic microorganisms. Among these are growth-promoting bacteria that support the growth and healthy development of their host macroalgae, and these macroalgae can be utilized in agriculture as biostimulants, offering an alternative to traditional agrochemicals. However, to date, no comparative studies have been conducted on the functional profile and bacterial diversity associated with coastal macroalgae of Peru. In this study, we employed amplicon sequencing of the V3-V4 region of 16S rRNA gene in twelve host macroalgae collected from two rocky shores in central Peru to compare their bacterial communities. The results revealed high bacterial diversity across both sites, but differences in microbial composition were noted. The phyla Bacteroidota and Pseudomonadota were predominant. The functional prediction highlighted 44 significant metabolic pathways associated with the bacterial microbiota when comparing host macroalgae. These active pathways are related to metabolism and genetic and cellular information processing. No direct association was detected between the macroalgal genera and the associated microbiota, suggesting that the bacterial community is largely influenced by their genetic functions than the taxonomic composition of their hosts. Furthermore, some species of Chlorophyta and Rhodophyta were observed to host growth-promoting bacteria, such as Maribacter sp. and Sulfitobacter sp.

Microbial community structure and metabolic profile of anthropized freshwater tributary channels from La Plata River, Argentina, to develop sustainable remediation strategies.

Microbial communities from freshwater sediments are involved in biogeochemical cycles and they can be modified by physical and chemical changes in the environment. Linking the microbial community structure (MCS) with physicochemistry of freshwater courses allows a better understanding of its ecology and can be useful to assess the ecological impact generated by human activity. The MCS of tributary channels from La Plata River affected by oil refinery (C, D, and E) and one also by urban discharges (C) was studied. For this purpose, 16S rRNA metabarcoding analysis, in silico metagenome functional prediction, and the hydrocarbon degradation potential (in silico predictions of hydrocarbon-degrading genes and their quantification by qPCR) of the MCS were studied. Principal coordinate analysis revealed that the MCS was different between sites, and it was not structured by the hydrocarbon content. Site C showed physicochemical characteristics, bacterial taxa, and an in silico functional prediction related to fermentative/heterotrophic metabolism. Site D, despite having higher concentration of hydrocarbon, presented autotrophic, syntrophic, and methanogenic pathways commonly involved in natural processes in anoxic sediments. Site E showed and intermediate autotrophic/heterotrophic behavior. The hydrocarbon degradation potential showed no positive correlation between the hydrocarbon-degrading genes quantified and predicted. The results suggest that the hydrocarbon concentration in the sites was not enough selection pressure to structure the bacterial community composition. Understanding which is the variable that structures the bacterial community composition is essential for monitoring and designing of sustainable management strategies for contaminated freshwater ecosystems.

Amino Acids in the Root Exudates of Agave lechuguilla Torr. Favor the Recruitment and Enzymatic Activity of Nutrient-Improvement Rhizobacteria.

Agave lechuguilla is a widely distributed plant in arid ecosystems. It has been suggested that its microbiome is partially responsible for its great adaptability to the oligotrophic environments of the Chihuahuan Desert. To lead the recruitment of beneficial rhizobacteria, the root exudates are essential; however, the amino acids contained within these compounds had been largely overlooked. Thus, we investigated how the variations of amino acids in the rhizosphere at different growth stages of A. lechuguilla affect the rhizobacterial community composition, its functions, and activity of the beneficial bacteria. In this regard, it was found that arginine and tyrosine were related to the composition of the rhizobacterial community associated to A. lechuguilla, where the most abundant genera were from the phylum Proteobacteria and Bacteroidetes. Moreover, Firmicutes was largely represented by Bacillus in the phosphorus-mineralizing bacteria community, which may indicate its great distribution and versatility in the harsh environments of the Chihuahuan Desert. In contrast, we found a high proportion of Unknown taxa of nitrogen-fixing bacteria, reflecting the enormous diversity in the rhizosphere of these types of plants that remains to be explored. This work also reports the influence of micronutrients and the amino acids methionine and arginine over the increased activity of the nitrogen-fixing and phosphorus-mineralizing bacteria in the rhizosphere of lechuguillas. In addition, the results highlight the multiple beneficial functions present in the microbiome that could help the host to tolerate arid conditions and improve nutrient availability.

The Role of Diversity in Mediating Microbiota Structural and Functional Differences in Two Sympatric Species of Abalone Under Stressed Withering Syndrome Conditions.

Withering syndrome (WS) is a gastro-intestinal (GI) infectious disease likely affecting all abalone species worldwide. Structural and functional changes in abalone GI microbiotas under WS-stressed conditions remain poorly investigated. It is unclear if interspecific microbiota differences, such as the presence of certain microbes, their abundance, and functional capabilities, may be involved in the occurrence of this disease. Bacterial microbiotas of healthy Haliotis fulgens and Haliotis corrugata are mainly composed by Tenericutes, Proteobacteria, Fusobacteria, and Spirochaetes. We previously reported species-specific structural and functional profiles of those communities and suggested that they are of consequence to the different susceptibility of each species to WS. Here, we address this question by comparing the structure and function of healthy and dysbiotic microbiota through 454 pyrosequencing and PICRUSt 2, respectively. Our findings suggest that the extent to which WS-stressed conditions may explain structural and functional differences in GI microbiota is contingent on the microbiota diversity itself. Indeed, microbiota differences between stressed and healthy abalone were marginal in the more complex bacterial communities of H. corrugata, in which no significant structural or functional changes were detected. Conversely, significant structural changes were observed in the less complex bacterial microbiota of H. fulgens. Moreover, structural alterations led to a significant downregulation of some metabolic activities conducted by GI bacteria. Accordingly, results suggest that gastro-intestinal bacterial diversity appears to be related with both the health of abalone and the etiology of WS.

Microbial community metabolic alterations and resistance to metals and antibiotics driven by chronic exposition to multiple pollutants in a highly impacted tropical coastal bay.

Microbial communities from Sepetiba Bay (SB, Rio de Janeiro, Brazil), characterized by 16S rRNA gene (V4-V5 region) sequencing analysis, were found to be correlated with the metallic contamination factor and the Quality Ratio (QR) index. Consistently, the predicted function of microbial communities, obtained with Tax4Fun2, showed that the functional patterns in SB internal sector under the highest anthropogenic pressure were different from that observed in the external sector with the lowest contamination level. Signal transduction, cellular community, membrane transport, and energy metabolism were among the KEGG pathways favored by metallic contamination in the SB internal sector, while lipid metabolism, transcription, and translation were among the pathways favored in the SB external sector. Noteworthy, the relative proportions of KEGG pathways and genes associated with metallic homeostasis showed significant differences according to the SB sectors, consistently with the ecological risk classification (QR index) of sediments. The functional prediction approach is an economically viable alternative and presents an overview of the main pathways/genes favored in the SB microbiota exposed to long-term pollution. In contrast, the microgAMBI, ecological status index based on bacterial community composition, was not consistent with the metallic contamination of SB, suggesting that this index requires improvements to be applied in tropical areas. Our study also revealed a strong correlation between metal resistance genes (MRG) and antibiotic resistance genes (ARG), indicating that MRG and ARG are co-selected by the metallic contamination prevailing in SB.

Bacteriome depiction and the trophic status of the largest Northern highland lake from Andes system: Lago de Tota, Boyacá, Colombia.

Lago de Tota is the largest highland lake in Colombia and one of the most remarkable of Northern Andean Mountain range. This lake is under an anthropogenic-based eutrophication process as a consequence of non-sustainable agriculture practices developing nearby. Notable relationship between the trophic status and Bacteriome loop dynamics has been increasingly disclosed in lakes worldwide. We performed a 16S sequencing analysis to depict the bacterial community present and we inferred its potential gene function in Lago de Tota. Parameters for determining current trophic condition such as total nitrogen (TN), dissolved carbon (DOC), particulate organic matter (POM), and chlorophyll-a (chl-a) were measured. A total of 440 Operational Taxonomic Units (OTUs) arranged into 50 classes were identified based on V3-V4 regions of the 16S rRNA gene, harboring high-frequent likely found environmental classes such as Actinobacteria, Gammaproteobacteria, Bacteroidia, Acidimicrobia, and Verrucomicrobiae. A total of 26 bacterial classes configure most abundant predicted functional processes involved in organic matter decomposition (i.e., carbohydrate metabolism, amino acid metabolism, xenobiotic biodegradation, and energy metabolism). In general, Actinobacteria, Alphaproteobacteria, and Gammaproteobacteria show the highest potential gene functional contributors, although other low-frequent classes OTUs are also relevant in processes of carbohydrate metabolism, xenobiotic biodegradation, and energy metabolism. The Trophic State Index indicates an oligo-mesotrophic status, and additional variables measured (i.e., POM, DOC) suggest the increasing carbon accumulation. Results provide preliminary evidence for several bacteria groups related to eutrophication of Lago de Tota. Under this picture, we suggest that further studies for Bacteriome loop spatial-temporal description are essential to inform local water quality monitoring strategies.

Assessment of Biological Contribution to Natural Recovery of Anthropized Freshwater Sediments From Argentina: Autochthonous Microbiome Structure and Functional Prediction.

Monitored natural recovery (MNR) is an in situ technique of conventional remediation for the treatment of contaminated sediments that relies on natural processes to reduce the bioavailability or toxicity of contaminants. Metabarcoding and bioinformatics approaches to infer functional prediction were applied in bottom sediments of a tributary drainage channel of Río de La Plata estuary, in order to assess the biological contribution to MNR. Hydrocarbon concentration in water samples and surface sediments was below the detection limit. Surface sediments were represented with high available phosphorous, alkaline pH, and the bacterial classes Anaerolineae, Planctomycetia, and Deltaproteobacteria. The functional prediction in surface sediments showed an increase of metabolic activity, carbon fixation, methanogenesis, and synergistic relationships between Archaeas, Syntrophobacterales, and Desulfobacterales. The prediction in non-surface sediments suggested the capacity to respond to different kinds of environmental stresses (oxidative, osmotic, heat, acid pH, and heavy metals), predicted mostly in Lactobacillales order, and the capacity of Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, and Actinomyces classes to degrade xenobiotic compounds. Canonical correspondence analysis (CCA) suggests that depth, phosphate content, redox potential, and pH were the variables that structured the bacterial community and not the hydrocarbons. The characterization of sediments by metabarcoding and functional prediction approaches, allowed to assess how the microbial activity would contribute to the recovery of the site.

In-depth assessment of microbial communities in the full-scale vertical flow treatment wetlands fed with raw domestic wastewater.

A multiphase study was proposed to examine microbial communities linked to the nitrogen cycle in the first stage of four full-scale French vertical flow treatment systems. To this end, denaturing gradient gel electrophoresis (DGGE) was performed for structural assessment and quantitative PCR (qPCR) to enumerate the abundance of ammonia-oxidizing (AOB). 16S rRNA sequencing was used to assess the taxonomic profile followed by putative assessment of functional genes. The samples were collected under different conditions, such as operational time (presence/absence of sludge layer on the surface of the filters), season (winter and summer), sampling depth (0, 15 and 30 cm) and operation cycle (rest and feed periods). A structural disparity was noted in the upper layers, whereas higher similarity at 30 cm was observed highlighting the effect of organic matter on bacterial diversity. The 7th rest day was highlighted by an apparent decline in the microbial community abundance. Additionally, qPCR indicated that the largest amount of AOB was found at 30 cm depth and during the feeding period. From the taxonomic profile, Mycobacterium, Acinetobacter, Flavobacterium, and Nitrospira were the most abundant genre found in all systems. The functional prediction results showed predicted genes linked to the denitrification process. The results suggested that operating time and season were responsible for the pattern of the microbial community behavior. This study allowed us to further understand the bacterial dynamics and to advance the idea of design modifications made in the first stage of the classical French system to improve nitrogen removal are promising.

Microbiome taxonomic and functional profiles of two domestic sewage treatment systems.

Anaerobic systems for domestic sewage treatment, like septic tanks and anaerobic filters, are used in developing countries due to favorable economic and functional features. The anaerobic filter is used for the treatment of the septic tank effluent, to improve the COD removal efficiency of the system. The microbial composition and diversity of the microbiome from two wastewater treatment systems (factory and rural school) were compared through 16S rRNA gene sequencing using MiSeq 2 × 250 bp Illumina sequencing platform. Additionally, 16S rRNA data were used to predict the functional profile of the microbial communities using PICRUSt2. Results indicated that hydrogenotrophic methanogens, like Methanobacterium, were found in higher abundance in both systems compared to acetotrophic methanogens belonging to Methanosaeta genus. Also, important syntrophic microorganisms (Smithella, Syntrophus, Syntrophobacter) were found in the factory and rural school wastewater treatment systems. Microbial communities were also compared between stages (septic tank and anaerobic filter) of each wastewater treatment stage, revealing that, in the case of the rural school, both microbial communities were quite similar most likely due to hydraulic short-circuit issues. Meanwhile, in the factory, microbial communities from the septic tank and anaerobic filter were different. The school system showed lower COD removal rates (2-30%), which were probably related to a higher abundance of Firmicutes members in addition to the hydraulic short-circuit and low abundance of Chloroflexi members. On the other hand, the fiberglass factory presented higher COD removal rates (60-83%), harboring phyla reported as the core microbiome of anaerobic digesters (Bacteroidetes, Chloroflexi, and Proteobacteria phyla). The knowledge of the structure and composition of wastewater treatment systems may provide support for the improvement of the pollutant removal in anaerobic process.

Differential effects on neurodevelopment of FTO variants in obesity and bipolar disorder suggested by in silico prediction of functional impact: An analysis in Mexican population.

INTRODUCTION: Several studies indicate that polygenic obesity is linked to fat-mass and obesity-associated (FTO) genetic variants. Nevertheless, the link between variants in FTO and mental disorders has been barely explored. The present work aims to determine whether FTO genetic variants are associated with bipolar disorder and obesity, and to perform an in silico prediction of variant-dependent functional impact on the developing brain transcriptome. METHODS: Four hundred and forty-six Mexican mestizos were included in a genetic association analysis. SNP-sequence kernel association test and linear mixed models were implemented for genetic association assessment. For functional impact prediction, we analyzed the mapping of regulatory elements, the modification of binding sites of transcription factors and the expression of transcription factors in the brain developing transcriptome, searching on different databases. RESULTS: In the set-based analysis, we found different associated regions to BD (bipolar disorder) and obesity. The promoter flanking region of FTO intron 1 was associated with differential effects on BMI, while intron 2 of RPGRIP1L and FTO upstream regions were associated with BD. The prediction analysis showed that FTO BD-associated variants disturb binding sites of SP1 and SP2; obesity-associated variants, on the other hand, disturb binding sites of FOXP1, which are transcription factors highly expressed during prenatal development stages of the brain. CONCLUSION: Our results suggest a possible effect of FTO variants on neurodevelopment in obesity and bipolar disorder, which gives new insights into the molecular mechanism underlying this association.

Functional metagenomics: a tool to gain knowledge for agronomic and veterinary sciences.

The increased global demand for food production has motivated agroindustries to increase their own levels of production. Scientific efforts have contributed to improving these production systems, aiding to solve problems and establishing novel conceptual views and sustainable alternatives to cope with the increasing demand. Although microorganisms are key players in biological systems and may drive certain desired responses toward food production, little is known about the microbial communities that constitute the microbiomes associated with agricultural and veterinary activities. Understanding the diversity, structure and in situ interactions of microbes, together with how these interactions occur within microbial communities and with respect to their environments (including hosts), constitutes a major challenge with an enormous relevance for agriculture and biotechnology. The emergence of high-throughput sequencing technologies, together with novel and more accessible bioinformatics tools, has allowed researchers to learn more about the functional potential and functional activity of these microbial communities. These tools constitute a relevant approach for understanding the metabolic processes that can occur or are currently occurring in a given system and for implementing novel strategies focused on solving production problems or improving sustainability. Several 'omics' sciences and their applications in agriculture are discussed in this review, and the usage of functional metagenomics is proposed to achieve substantial advances for food agroindustries and veterinary sciences.

Biostatistical approaches for the reconstruction of gene co-expression networks based on transcriptomic data.

Techniques in molecular biology have permitted the gathering of an extremely large amount of information relating organisms and their genes. The current challenge is assigning a putative function to thousands of genes that have been detected in different organisms. One of the most informative types of genomic data to achieve a better knowledge of protein function is gene expression data. Based on gene expression data and assuming that genes involved in the same function should have a similar or correlated expression pattern, a function can be attributed to those genes with unknown functions when they appear to be linked in a gene co-expression network (GCN). Several tools for the construction of GCNs have been proposed and applied to plant gene expression data. Here, we review recent methodologies used for plant gene expression data and compare the results, advantages and disadvantages in order to help researchers in their choice of a method for the construction of GCNs.