Melipona stingless bees and honey microbiota reveal the diversity, composition, and modes of symbionts transmission.

The Melipona gut microbiota differs from other social bees, being characterized by the absence of crucial corbiculate core gut symbionts and a high occurrence of environmental strains. We studied the microbial diversity and composition of three Melipona species and their honey to understand which strains are obtained by horizontal transmission (HT) from the pollination environment, represent symbionts with HT from the hive/food stores or social transmission (ST) between nestmates. Bees harbored higher microbial alpha diversity and a different and more species-specific bacterial composition than honey. The fungal communities of bee and honey samples are also different but less dissimilar. As expected, the eusocial corbiculate core symbionts Snodgrassella and Gilliamella were absent in bees that had a prevalence of Lactobacillaceae - including Lactobacillus (formerly known as Firm-5), Bifidobacteriaceae, Acetobacteraceae, and Streptococcaceae - mainly strains close to Floricoccus, a putative novel symbiont acquired from flowers. They might have co-evolved with these bees via ST, and along with environmental Lactobacillaceae and Pectinatus (Veillonellaceae) strains obtained by HT, and Metschnikowia and Saccharomycetales yeasts acquired by HT from honey or the pollination environment, including plants/flowers, possibly compose the Melipona core microbiota. This work contributes to the understanding of Melipona symbionts and their modes of transmission.

Machine learning-based soil quality assessment for enhancing environmental monitoring in iron ore mining-impacted ecosystems.

In November 2015, a catastrophic rupture of the Fundão dam in Mariana (Brazil), resulted in extensive socio-economic and environmental repercussions that persist to this day. In response, several reforestation programs were initiated to remediate the impacted regions. However, accurately assessing soil health in these areas is a complex endeavor. This study employs machine learning techniques to predict soil quality indicators that effectively differentiate between the stages of recovery in these areas. For this, a comprehensive set of soil parameters, encompassing 3 biological, 16 chemical, and 3 physical parameters, were evaluated for samples exposed to mining tailings and those unaffected, totaling 81 and 6 samples, respectively, which were evaluated over 2 years. The most robust model was the decision tree with a restriction of fewer levels to simplify the tree structure. In this model, Cation Exchange Capacity (CEC), Microbial Biomass Carbon (MBC), Base Saturation (BS), and Effective Cation Exchange Capacity (eCEC) emerged as the most pivotal factors influencing model fitting. This model achieved an accuracy score of 92% during training and 93% during testing for determining stages of recovery. The model developed in this study has the potential to revolutionize the monitoring efforts conducted by regulatory agencies in these regions. By reducing the number of parameters that necessitate evaluation, this enhanced efficiency promises to expedite recovery monitoring, simultaneously enhancing cost-effectiveness while upholding the analytical rigor of assessments.

Characterization of the biofilm structure and microbial diversity of sulfate-reducing bacteria from petroleum produced water supplemented by different carbon sources.

Colonization by sulfate-reducing bacteria (SRB) in environments associated with oil is mainly dependent on the availability of sulfate and carbon sources. The formation of biofilms by SRB increases the corrosion of pipelines and oil storage tanks, representing great occupational and operational risks and respective economic losses for the oil industry. The aim of this study was to evaluate the influence of the addition of acetate, butyrate, lactate, propionate and oil on the structure of biofilm formed in carbon steel coupons, as well as on the diversity of total bacteria and SRB in the planktonic and sessile communities from petroleum produced water. The biofilm morphology, chemical composition, average roughness and the microbial diversity was analyzed. In all carbon sources, formation of dense biofilm without morphological and/or microbial density differences was detected, with the most of cells observed in the form of individual rods. The diversity and richness indices of bacterial species in the planktonic community was greater than in the biofilm. Geotoga was the most abundant genus, and more than 85% of SRB species were common to all treatments. The functional predicted profile shown that the observed genres in planktonic communities were related to the reduction of sulfate, sulfite, elementary sulfur and other sulfur compounds, but the abundance varied between treatments. For the biofilm, the functions predicted profile for the oil treatment was the one that most varied in relation to the control, while for the planktonic community, the addition of all carbon sources interfered in the predicted functional profile. Thus, although it does not cause changes in the structure and morphology biofilm, the supplementation of produced water with different carbon sources is associated with changes in the SRB taxonomic composition and functional profiles of the biofilm and the planktonic bacterial communities.

Physicochemical characterization of Pseudomonas stutzeri UFV5 and analysis of its transcriptome under heterotrophic nitrification/aerobic denitrification pathway induction condition.

Biological ammonium removal via heterotrophic nitrification/aerobic denitrification (HN/AD) presents several advantages in relation to conventional removal processes, but little is known about the microorganisms and metabolic pathways involved in this process. In this study, Pseudomonas stutzeri UFV5 was isolated from an activated sludge sample from oil wastewater treatment station and its ammonium removal via HN/AD was investigated by physicochemical and molecular approaches to better understand this process and optimize the biological ammonium removal in wastewater treatment plants. Results showed that P. stutzeri UFV5 removed all the ammonium in 48-72 hours using pyruvate, acetate, citrate or sodium succinate as carbon sources, C/N ratios 6, 8, 10 and 12, 3-6% salinities, pH 7-9 and temperatures of 20-40 °C. Comparative genomics and PCR revealed that genes encoding the enzymes involved in anaerobic denitrification process are present in P. stutzeri genome, but no gene that encodes enzymes involved in autotrophic nitrification was found. Furthermore, transcriptomics showed that none of the known enzymes of autotrophic nitrification and anaerobic denitrification had their expression differentiated and an upregulation of the biosynthesis machinery and protein translation was observed, besides several genes with unknown function, indicating a non-conventional mechanism involved in HN/AD process.

Effect of the gradual increase of salt on stability and microbial diversity of granular sludge and ammonia removal.

Two sequential batch reactors were operated, aiming at forming aerobic granular sludge and studying the effects of the gradual increase of the NaCl concentration on the granule. structure and microbial diversity, and on the efficiency of ammonia removal. The reactors were fed with ammonia-enriched synthetic effluent and 5 g L-1 of NaCl per week were applied. A decrease in the size of the granules was observed until they were completely disintegrated as the salt concentration increased up to 10 g L-1. However, the ammonia removal efficiency remained high in all the salinities applied. By sequencing the 16S rRNA amplicon gene, the microbial community structure allowed the verification of the presence of several genera affiliated with the bacteria that perform both heterotrophic nitrification and aerobic denitrification, besides those involved in the conventional nitrification and denitrification and the ANAMMOX process. Salinity affected the microbial population related to the formation and stability of the granules.