Analysing the dynamics of the bacterial community in pozol, a Mexican fermented corn dough

Pozol is a traditional prehispanic Mexican beverage made from fermented nixtamal dough; it is still part of everyday life in many communities due to its nutritional properties. It is the product of spontaneous fermentation and has a complex microbiota composed primarily of lactic acid bacteria (LAB). Although this is a beverage that has been used for centuries, the microbial processes that participate in this fermented beverage are not well understood. We fermented corn dough to produce pozol and sampled it at four key times to follow the community and metabolic changes (0, 9 24 and 48 h) by shotgun metagenomic sequencing to determine structural changes in the bacterial community, as well as metabolic genes used for substrate fermentation, nutritional properties and product safety. We found a core of 25 abundant genera throughout the 4 key fermentation times, with the genus Streptococcus being the most prevalent throughout fermentation. We also performed an analysis focused on metagenomic assembled genomes (MAGs) to identify species from the most abundant genera. Genes involving starch, plant cell wall (PCW), fructan and sucrose degradation were found throughout fermentation and in MAGs, indicating the metabolic potential of the pozol microbiota to degrade these carbohydrates. Complete metabolic modules responsible for amino acid and vitamin biosynthesis increased considerably during fermentation, and were also found to be abundant in MAG, highlighting the bacterial contribution to the well-known nutritional properties attributed to pozol. Further, clusters of genes containing CAZymes (CGCs) and essential amino acids and vitamins were found in the reconstructed MAGs for abundant species in pozol. The results of this study contribute to our understanding of the metabolic role of micro-organisms in the transformation of corn to produce this traditional beverage and their contribution to the nutritional impact that pozol has had for centuries in the traditional cuisine of southeast Mexico.

Metagenomic analysis and antibacterial activity of kefir microorganisms

The microbiota composition of kefir grain and milk kefir was assessed via a metagenomic approach. Significant microorganisms were isolated and identified using molecular methods. A safety assessment was conducted based on antibiotic susceptibility and blood hemolysis. Probiotic traits such as resistance to gastric tract conditions, surface characteristics, adhesion to intestinal cells, and antibacterial activity were also assessed. Metagenomic analysis revealed that kefir grains are a more stable community with clear dominant species as compared to milk kefir. Lactobacillus kefiranofaciens BDGO-A1, Lactobacillus helveticus BDGO-AK2, and Lactobacillu kefiri strains showed tolerance to acidic pH and the presence of bile salts, adhesion capability to Caco-2 cells, in vitro antibacterial activity, and the production of antibacterial proteins. In the metagenomic analysis, contigs associated with these species showed the presence of genes involved in exporting polyketide antibiotics and bacteriocin production. To fully exploit the potential probiotic properties of these microorganisms to help human health, further investigation is necessary to elucidate the mechanisms behind the biological activity and the genotypic characteristics of the isolated strains.

Revisiting Microbial Diversity in Hypersaline Microbial Mats from Guerrero Negro for a Better Understanding of Methanogenic Archaeal Communities

Knowledge regarding the diversity of methanogenic archaeal communities in hypersaline environments is limited because of the lack of efficient cultivation efforts as well as their low abundance and metabolic activities. In this study, we explored the microbial communities in hypersaline microbial mats. Bioinformatic analyses showed significant differences among the archaeal community structures for each studied site. Taxonomic assignment based on 16S rRNA and methyl coenzyme-M reductase (mcrA) gene sequences, as well as metagenomic analysis, corroborated the presence of Methanosarcinales. Furthermore, this study also provided evidence for the presence of Methanobacteriales, Methanomicrobiales, Methanomassiliicoccales, Candidatus Methanofastidiosales, Methanocellales, Methanococcales and Methanopyrales, although some of these were found in extremely low relative abundances. Several mcrA environmental sequences were significantly different from those previously reported and did not match with any known methanogenic archaea, suggesting the presence of specific environmental clusters of methanogenic archaea in Guerrero Negro. Based on functional inference and the detection of specific genes in the metagenome, we hypothesised that all four methanogenic pathways were able to occur in these environments. This study allowed the detection of extremely low-abundance methanogenic archaea, which were highly diverse and with unknown physiology, evidencing the presence of all methanogenic metabolic pathways rather than the sheer existence of exclusively methylotrophic methanogenic archaea in hypersaline environments.

MGnify: the microbiome sequence data analysis resource in 2023

The MGnify platform (https://www.ebi.ac.uk/metagenomics) facilitates the assembly, analysis and archiving of microbiome-derived nucleic acid sequences. The platform provides access to taxonomic assignments and functional annotations for nearly half a million analyses covering metabarcoding, metatranscriptomic, and metagenomic datasets, which are derived from a wide range of different environments. Over the past 3 years, MGnify has not only grown in terms of the number of datasets contained but also increased the breadth of analyses provided, such as the analysis of long-read sequences. The MGnify protein database now exceeds 2.4 billion non-redundant sequences predicted from metagenomic assemblies. This collection is now organised into a relational database making it possible to understand the genomic context of the protein through navigation back to the source assembly and sample metadata, marking a major improvement. To extend beyond the functional annotations already provided in MGnify, we have applied deep learning-based annotation methods. The technology underlying MGnify's Application Programming Interface (API) and website has been upgraded, and we have enabled the ability to perform downstream analysis of the MGnify data through the introduction of a coupled Jupyter Lab environment.

Definition of the Metagenomic Profile of Ocean Water Samples From the Gulf of Mexico Based on Comparison With Reference Samples From Sites Worldwide

Computational and statistical analysis of shotgun metagenomes can predict gene abundance and is helpful for elucidating the functional and taxonomic compositions of environmental samples. Gene products are compared against physicochemical conditions or perturbations to shed light on the functions performed by the microbial community of an environmental sample; however, this information is not always available. The present study proposes a method for inferring the metabolic potential of metagenome samples by constructing a reference based on determining the probability distribution of the counts of each enzyme annotated. To test the methodology, we used marine water samples distributed worldwide as references. Then, the references were utilized to compare the annotated enzymes of two different water samples extracted from the Gulf of Mexico (GoM) to distinguish those enzymes with atypical behavior. The enzymes whose annotation counts presented frequencies significantly different from those of the reference were used to perform metabolic reconstruction, which naturally identified pathways. We found that several of the enzymes were involved in the biodegradation of petroleum, which is consistent with the impact of human hydrocarbon extraction activity and its ubiquitous presence in the GoM. The examination of other reconstructed pathways revealed significant enzymes indicating the presence of microbial communities characterizing each ocean depth and ocean cycle, providing a fingerprint of each sampled site.

Identification of Putative β-Galactosidase Genes in the Genome of Lactobacillus helveticus OSU-PECh-4A

The Lactobacillus helveticus OSU-PECh-4A strain, from the Ohio State University Parker Chair collection, produces exceptional β-galactosidase activity using acid whey as a culture medium, compared with a commercial broth. The strain has a genome sequence of 1,834,843 bp, and its GC content is 36.69%. Using InterProScan v5.50-84.0 software, four genes with putative β-galactosidase function were found.

Distinctive prokaryotic microbiomes in sympatric plant roots from a Yucatan cenote

OBJECTIVE

Cenotes are flooded caves in Mexico's Yucatan peninsula. Many cenotes are interconnected in an underground network of pools and streams forming a vast belowground aquifer across most of the peninsula. Many plants in the peninsula grow roots that reach the cenotes water and live submerged in conditions similar to hydroponics. Our objective was to study the microbial community associated with these submerged roots of the Sac Actun cenote. We accomplished this objective by profiling the root prokaryotic community using 16S rRNA gene amplification and sequencing.

RESULTS

We identified plant species by DNA barcoding the total genomic DNA of each root. We found a distinctive composition of the root and water bacterial and archaeal communities. Prokaryotic diversity was higher in all plant roots than in the surrounding freshwater, suggesting that plants in the cenotes may attract and select microorganisms from soil and freshwater, and may also harbor vertically transmitted lineages. The reported data are of interest for studies targeting biodiversity in general and root-microbial ecological interactions specifically.

Paenarthrobacter sp. GOM3 Is a Novel Marine Species With Monoaromatic Degradation Relevance

Paenarthrobacter sp. GOM3, which is a strain that represents a new species-specific context within the genus Paenarthrobacter, is clearly a branched member independent of any group described thus far. This strain was recovered from marine sediments in the Gulf of Mexico, and despite being isolated from a consortium capable of growing with phenanthrene as a sole carbon source, this strain could not grow successfully in the presence of this substrate alone. We hypothesized that the GOM3 strain could participate in the assimilation of intermediate metabolites for the degradation of aromatic compounds. To date, there are no experimental reports of Paenarthrobacter species that degrade polycyclic aromatic hydrocarbons (PAHs) or their intermediate metabolites. In this work, we report genomic and experimental evidence of metabolic benzoate, gentisate, and protocatechuate degradation by Paenarthrobacter sp. GOM3. Gentisate was the preferred substrate with the highest volumetric consumption rate, and genomic analysis revealed that this strain possesses multiple gene copies for the specific transport of gentisate. Furthermore, upon analyzing the GOM3 genome, we found five different dioxygenases involved in the activation of aromatic compounds, suggesting its potential for complete remediation of PAH-contaminated sites in combination with strains capable of assimilating the upper PAH degradation pathway. Additionally, this strain was characterized experimentally for its pathogenic potential and in silico for its antimicrobial resistance. An overview of the potential ecological role of this strain in the context of other members of this taxonomic clade is also reported.

Metagenomic Profiling and Microbial Metabolic Potential of Perdido Fold Belt (NW) and Campeche Knolls (SE) in the Gulf of Mexico

The Gulf of Mexico (GoM) is a particular environment that is continuously exposed to hydrocarbon compounds that may influence the microbial community composition. We carried out a metagenomic assessment of the bacterial community to get an overall view of this geographical zone. We analyzed both taxonomic and metabolic markers profiles to explain how the indigenous GoM microorganims participate in the biogeochemical cycling. Two geographically distant regions in the GoM, one in the north-west (NW) and one in the south-east (SE) of the GoM were analyzed and showed differences in their microbial composition and metabolic potential. These differences provide evidence the delicate equilibrium that sustains microbial communities and biogeochemical cycles. Based on the taxonomy and gene groups, the NW are more oxic sediments than SE ones, which have anaerobic conditions. Both water and sediments show the expected sulfur, nitrogen, and hydrocarbon metabolism genes, with particularly high diversity of the hydrocarbon-degrading ones. Accordingly, many of the assigned genera were associated with hydrocarbon degradation processes, Nitrospira and Sva0081 were the most abundant in sediments, while Vibrio, Alteromonas, and Alcanivorax were mostly detected in water samples. This basal-state analysis presents the GoM as a potential source of aerobic and anaerobic hydrocarbon degradation genes important for the ecological dynamics of hydrocarbons and the potential use for water and sediment bioremediation processes.

Bacterial Diversity and the Geochemical Landscape in the Southwestern Gulf of Mexico

Marine sediments are an example of one of the most complex microbial habitats. These bacterial communities play an important role in several biogeochemical cycles in the marine ecosystem. In particular, the Gulf of Mexico has a ubiquitous concentration of hydrocarbons in its sediments, representing a very interesting niche to explore. Additionally, the Mexican government has opened its oil industry, offering several exploration and production blocks in shallow and deep water in the southwestern Gulf of Mexico (swGoM), from which there are no public results of conducted studies. Given the higher risk of large-scale oil spills, the design of contingency plans and mitigation activities before oil exploitation is of growing concern. Therefore, a bacterial taxonomic baseline profile is crucial to understanding the impact of any eventual oil spill. Here, we show a genus level taxonomic profile to elucidate the bacterial baseline, pointing out richness and relative abundance, as well as relationships with 79 abiotic parameters, in an area encompassing ∼150,000 km2, including a region where the exploitation of new oil wells has already been authorized. Our results describe for the first time the bacterial landscape of the swGoM, establishing a bacterial baseline "core" of 450 genera for marine sediments in this region. We can also differentiate bacterial populations from shallow and deep zones of the swGoM based on their community structure. Shallow sediments have been chronically exposed to aromatic hydrocarbons, unlike deep zones. Our results reveal that the bacterial community structure is particularly enriched with hydrocarbon-degrading bacteria in the shallow zone, where a greater aromatic hydrocarbon concentration was determined. Differences in the bacterial communities in the swGoM were also observed through a comprehensive comparative analysis relative to various marine sediment sequencing projects, including sampled sites from the Deep Water Horizon oil spill. This study in the swGoM provides clues to the bacterial population adaptation to the ubiquitous presence of hydrocarbons and reveals organisms such as Thioprofundum bacteria with potential applications in ecological surveillance. This resource will allow us to differentiate between natural conditions and alterations generated by oil extraction activities, which, in turn, enables us to assess the environmental impact of such activities.

Bacterial and archaeal profiling of hypersaline microbial mats and endoevaporites, under natural conditions and methanogenic microcosm experiments

Bacterial and archaeal community structure of five microbial communities, developing at different salinities in Baja California Sur, Mexico, were characterized by 16S rRNA sequencing. The response of the microbial community to artificial changes in salinity-sulfate concentrations and to addition of trimethylamine was also evaluated in microcosm experiments. Ordination analyses of the microbial community structure showed that microbial composition was distinctive for each hypersaline site. Members of bacteria were dominated by Bacteroidetes and Proteobacteria phyla, while Halobacteria of the Euryarchaeota phylum was the most represented class of archaea for all the environmental samples. At a higher phylogenetic resolution, methanogenic communities were dominated by members of the Methanosarcinales, Methanobacteriales and Methanococcales orders. Incubation experiments showed that putative hydrogenotrophic methanogens of the Methanomicrobiales increased in abundance only under lowest salinity and sulfate concentrations. Trimethylamine addition effectively increased the abundance of methylotrophic members from the Methanosarcinales, but also increased the relative abundance of the Thermoplasmata class, suggesting the potential capability of these microorganisms to use trimethylamine in hypersaline environments. These results contribute to the knowledge of microbial diversity in hypersaline environments from Baja California Sur, Mexico, and expand upon the available information for uncultured methanogenic archaea in these ecosystems.

The Road to Metagenomics: From Microbiology to DNA Sequencing Technologies and Bioinformatics

The study of microorganisms that pervade each and every part of this planet has encountered many challenges through time such as the discovery of unknown organisms and the understanding of how they interact with their environment. The aim of this review is to take the reader along the timeline and major milestones that led us to modern metagenomics. This new and thriving area is likely to be an important contributor to solve different problems. The transition from classical microbiology to modern metagenomics studies has required the development of new branches of knowledge and specialization. Here, we will review how the availability of high-throughput sequencing technologies has transformed microbiology and bioinformatics and how to tackle the inherent computational challenges that arise from the DNA sequencing revolution. New computational methods are constantly developed to collect, process, and extract useful biological information from a variety of samples and complex datasets, but metagenomics needs the integration of several of these computational methods. Despite the level of specialization needed in bioinformatics, it is important that life-scientists have a good understanding of it for a correct experimental design, which allows them to reveal the information in a metagenome.