Publications by authors named "Ulisses N da Rocha"
The introduction of antibiotic-resistant bacteria into riverine systems through the discharge of wastewater treatment plant (WWTP) effluent and agricultural waste poses significant health risks. Even when not pathogenic, these bacteria can act as reservoirs for antibiotic resistance genes (ARGs), transferring them to pathogens that infect humans and animals. In this study, we used fluorescence hybridization, qPCR, and metagenomics to investigate how anthropogenic activities affect microbial abundance and the resistome along the Holtemme River, a small river in Germany, from near-pristine to human-impacted sites.
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- - This study analyzed the microbial communities (bacteria, methanogenic archaea, and eukaryotes) in the guts of Pachnoda marginata larvae, specifically comparing the midgut and hindgut using sequencing methods.
- - The composition of these microbial communities varied significantly between gut sections and was influenced by the larvae's diet, with different bacterial families dominating in the midgut depending on whether they fed on leaves or straw.
- - Methanogenic communities also differed between gut compartments, showing higher diversity in the midgut compared to the hindgut, which was more specialized to the host; midgut communities resembled those found in the surrounding soil.
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- The study investigates the complex interactions between two bacterial species commonly found together in severe, difficult-to-treat infections.
- Researchers used both laboratory experiments and modeling to reveal how one species can partially inhibit the other and how they engage in a cross-feeding relationship, where one provides nutrients to support the other's growth.
- The findings enhance understanding of how these bacteria coexist and interact in polymicrobial infections, which could lead to new treatment strategies.
Machine Learning (ML) algorithms have been important tools for the extraction of useful knowledge from biological sequences, particularly in healthcare, agriculture, and the environment. However, the categorical and unstructured nature of these sequences requiring usually additional feature engineering steps, before an ML algorithm can be efficiently applied. The addition of these steps to the ML algorithm creates a processing pipeline, known as end-to-end ML.
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- Metagenomics allows scientists to analyze environmental DNA for insights into microbiomes, but eukaryotic organisms like fungi are often underrepresented due to challenges with intron-rich genes.
- Researchers developed a machine learning algorithm, SVMmycointron, to accurately predict fungal introns, improving gene annotations in metagenomic datasets by up to 9.1%.
- This tool enhances understanding of the role of fungi and other eukaryotes in microbiome function and is accessible for researchers working with metagenomics data.
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- The study investigates how changes in pH affect microbial communities involved in chain elongation processes in anaerobic bioreactors, focusing on their composition and performance in producing medium-chain carboxylates.
- Results show that increasing pH from 5.5 to 6.5 significantly alters community structure but does not permanently affect product yields, indicating a capacity for recovery following environmental shifts.
- Analyses revealed distinct pH preferences among key microbial species, revealing complex interactions within the community and highlighting the resilience and adaptability of these mixed cultures in fermentation pathways despite environmental changes.
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- - The study highlights the lack of regulations on antibiotic discharges from wastewater treatment plants (WWTP) into rivers, which allows for the persistence of antibiotic resistance genes (ARGs) in surface waters.
- - Using advanced techniques like quantitative PCR and nanopore sequencing, the researchers tracked the levels of specific ARGs and sulfonamides in river water, noting that WWTP effluent was the main source of these contaminants.
- - The findings indicated that downstream from the WWTP, water quality improved with decreasing concentrations of sulfonamides and ARGs, but an unexpected increase in the relative abundance of certain genes suggested potential gene multiplication in the river system.
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- * Researchers combined flow cytometry cell sorting with bioinformatics to classify cells from a wastewater microbial community into different abundance groups and sequenced their genomes.
- * Results showed a significant increase in species identification (two-fold improvement), revealing that sorting allows the recovery of genomes that are otherwise undetected in unsorted samples.
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- Cyanobacteria are gaining attention in biotechnology, particularly for genetic engineering and innovative reactor designs like capillary biofilm reactors (CBRs), which enhance cell growth.
- Strain PCC 7712 has been identified as ideal for CBRs due to its excellent biofilm attachment and high biomass yield, prompting the complete genome sequencing of both PCC 7712 and a related strain, PCC 7601.
- Despite their nearly identical genomes, differences in protein-coding sequences and nitrogen fixation abilities were observed between the two strains, indicating potential for targeted strain engineering.
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- * This study examined the carbohydrate utilization abilities of over 7000 bacterial and archaeal taxa using the Genomes from Earth's Microbiomes (GEM) catalog, revealing significant variation in enzyme production among different microbial groups and habitats.
- * The research highlighted that specific habitats, like plant-associated environments, harbor diverse carbohydrate-active enzymes, which could help predict microbial functions and identify important carbohydrate resources in various ecosystems.
Recent technological advances have led to an exponential expansion of biological sequence data and extraction of meaningful information through Machine Learning (ML) algorithms. This knowledge has improved the understanding of mechanisms related to several fatal diseases, e.g.
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- The study focuses on the microbial communities found in deep-sea iron-manganese (Fe-Mn) deposits, which are being impacted by mining activities.
- Researchers analyzed samples from two Atlantic Ocean locations, discovering unique microbial taxa and lower diversity compared to Pacific deposits.
- The findings emphasize the role of microbes in biogeochemical processes and highlight the need for understanding these communities before deep-sea mining occurs.
Aims: How benzene is metabolized by microbes under anoxic conditions is not fully understood. Here, we studied the degradation pathways in a benzene-mineralizing, nitrate-reducing enrichment culture.
Methods And Results: Benzene mineralization was dependent on the presence of nitrate and correlated to the enrichment of a Peptococcaceae phylotype only distantly related to known anaerobic benzene degraders of this family.
Deadwood represents significant carbon (C) stock in a temperate forests. Its decomposition and C mobilization is accomplished by decomposer microorganisms - fungi and bacteria - who also supply the foodweb of commensalist microbes. Due to the ecosystem-level importance of deadwood habitat as a C and nutrient stock with significant nitrogen fixation, the deadwood microbiome composition and function are critical to understanding the microbial processes related to its decomposition.
View Article and Find Full Text PDFA key question in microbial ecology is what the driving forces behind the persistence of large biodiversity in natural environments are. We studied a microbial community with more than 100 different types of species which evolved in a 15-years old bioreactor with benzene as the main carbon and energy source and nitrate as the electron acceptor. Using genome-centric metagenomics plus metatranscriptomics, we demonstrate that most of the community members likely feed on metabolic left-overs or on necromass while only a few of them, from families Rhodocyclaceae and Peptococcaceae, are candidates to degrade benzene.
View Article and Find Full Text PDFHigh-temperature aquifer thermal energy storage (HT-ATES) is a promising technique to reduce the CO2 footprint of heat supply in the frame of transitioning to renewable energies. However, HT-ATES causes temperature fluctuations in groundwater ecosystems potentially affecting important microbial-mediated ecosystem services. Hence, assessing the impact of increasing temperatures on the structure and functioning of aquifer microbiomes is crucial to evaluate potential environmental risks associated with HT-ATES.
View Article and Find Full Text PDFPlasmid transfers among bacterial populations can directly influence the ecological adaptation of these populations and their interactions with host species and environment. In this study, we developed a selective multiply-primed rolling circle amplification (smRCA) approach to enrich and characterize circular plasmid DNA from sponge microbial symbionts via high-throughput sequencing (HTS). DNA (plasmid and total community DNA) obtained from sponge (Cinachyrella sp.
View Article and Find Full Text PDFWe report three metagenome-assembled genomes (MAGs) of strains from coastal seawater (Portugal) to help illuminate the functions of understudied bacteria in marine environments. The MAGs encode proteins involved in aerobic anoxygenic photosynthesis and a versatile carbohydrate metabolism, strengthening the role of species in oceanic carbon cycling.
View Article and Find Full Text PDFMicrobiome studies focused on the genetic potential of microbial communities (metagenomics) became standard within microbial ecology. MG-RAST and the Sequence Read Archive (SRA), the two main metagenome repositories, contain over 202 858 public available metagenomes and this number has increased exponentially. However, mining databases can be challenging due to misannotated, misleading and decentralized data.
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- Lindane, a previously widely used pesticide, was banned in 2009 but still contaminates soil with high residues of HCH isomers.
- A study using two laboratory-scale reactors tested a combination of phytoremediation and anaerobic digestion (AD) to safely treat contaminated biomass.
- The results indicated that γ- and α-HCH were effectively transformed into chlorobenzene and benzene, while β-HCH remained, and specific microorganisms were identified as potential bioindicators for ongoing HCH degradation in the AD process.
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- The increase in antibiotic-resistant pathogens has created a pressing demand for new antimicrobial treatments, paving the way for innovative discovery methods utilizing next-generation sequencing.
- By analyzing the microbial diversity in 13 soil samples from various regions, researchers explored the genetic foundations of polyketides (PK) and non-ribosomal peptides (NRP), identifying lesser-known bacterial groups that could yield new antimicrobial compounds.
- Notably, the study revealed that certain soil samples, particularly from Antarctica, contained unique genetic sequences linked to PK and NRP biosynthesis, indicating a promising source for future drug development.
Marine sponges are early-branching, filter-feeding metazoans that usually host complex microbiomes comprised of several, currently uncultivatable symbiotic lineages. Here, we use a low-carbon based strategy to cultivate low-abundance bacteria from Spongia officinalis. This approach favoured the growth of Alphaproteobacteria strains in the genera Anderseniella, Erythrobacter, Labrenzia, Loktanella, Ruegeria, Sphingorhabdus, Tateyamaria and Pseudovibrio, besides two likely new genera in the Rhodobacteraceae family.
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