Bioactives of Melipona rufiventris Propolis: Exploring its Antimicrobial, Anti-Inflammatory, and Antioxidant Activities.

This study explores the potential of propolis, a resinous substance produced by bees, from Melipona rufiventris species. With its composition encompassing resin, wax, pollen, and soil, propolis holds historical significance in traditional medicine within tropical regions. This research is driven by the scarcity of information surrounding M. rufiventris propolis, prompting an investigation into its chemical constituents, in vivo toxicity, and antimicrobial, antioxidant, and anti-inflammatory properties. This exploration could potentially uncover novel applications for this natural product, bolstering both meliponiculture practices and the preservation of native bee populations. The propolis was sampled in Cabo Verde-MG and underwent ethanolic extraction to yield an extract (EEP) for analysis. Chemical assessments (Folin-Ciocalteau, and UHPLC-HRMS) revealed the presence of polyphenols, including flavonoids. The EEP demonstrated higher antimicrobial activity against Gram-positive bacteria and exhibited efficacy against multiresistant strains isolated from complex wounds. Synergistic interactions with commercial antibiotics were also observed. Furthermore, anti-inflammatory evaluations showcased the EEP's potential in reducing NF-kB activation and TNF-α release at non-toxic concentrations. Despite these promising biological activities, the EEP exhibited no antiproliferative effects and demonstrated safety in both the MTS assay and the G. mellonella model. Collectively, these findings highlight the M. rufiventris propolis extract as a valuable reservoir of bioactive compounds with multifaceted potential.

Effects of 5-year experimental warming in the Alpine belt on soil Archaea: Multi-omics approaches and prospects.

We currently lack a predictive understanding of how soil archaeal communities may respond to climate change, particularly in Alpine areas where warming is far exceeding the global average. Here, we characterized the abundance, structure, and function of total (by metagenomics) and active soil archaea (by metatranscriptomics) after 5-year experimental field warming (+1°C) in Italian Alpine grasslands and snowbeds. Our multi-omics approach unveiled an increasing abundance of Archaea during warming in snowbeds, which was negatively correlated with the abundance of fungi (by qPCR) and micronutrients (Ca and Mg), but positively correlated with soil water content. In the snowbeds transcripts, warming resulted in the enrichment of abundances of transcription and nucleotide biosynthesis. Our study provides novel insights into possible changes in soil Archaea composition and function in the climate change scenario.

Translation, cross-cultural adaptation, and validation of the Athlete Fear Avoidance Questionnaire (AFAQ) into Brazilian Portuguese.

BACKGROUND: Psychological factors play an important role in the adequate return of an athlete to sport. Our aim was to perform the translation, cross-cultural adaptation, and validation of the Athlete Fear Avoidance Questionnaire (AFAQ) into Brazilian Portuguese. METHODS: We performed the translation and cross-cultural adaptation and evaluated the structural validity, construct validity, and test-retest reliability. In addition to the AFAQ, we used the Numerical Pain Scale (NPS), Pain-Related Catastrophizing Thoughts Scale (PCTS), Self-Estimated Functional Inability because of Pain Questionnaire for athletes (SEFIP-sport), and Hospital Anxiety and Depression Scale (HADS). We used the exploratory factor analysis (EFA) to analyze the internal structure of the AFAQ. We used the Spearman's correlation coefficient (rho) to determine the magnitude of correlation between the AFAQ and the other instruments. We evaluated the test-retest reliability and internal consistency by means of intraclass correlation coefficient (ICC) and Cronbach's alpha, respectively. RESULTS: No adaptation was necessary to produce the AFAQ version in Brazilian Portuguese. We included 160 participants in the study. We identified the one-dimensionality of the AFAQ through the EFA with the implementation of parallel analysis (KMO = 0.83, p < 0.001 in Bartlett's Sphericity test). In construct validity, the magnitudes of correlation between the AFAQ and the other instruments ranged from 0.257 to 0.548. We identified adequate reliability (ICC = 0.85) and internal consistency (Cronbach's alpha = 0.90). CONCLUSION: The Brazilian version of the AFAQ with one domain and 10 items has adequate measurement properties in injured professional and recreational athletes.

Barthel Index is a valid and reliable tool to measure the functional independence of cancer patients in palliative care.

BACKGROUND: Our objective was to verify the reliability, internal consistency and construct validity of the Barthel Index in Brazilian cancer patients in palliative care. METHODS: We included patients with cancer, both sexes, and age greater than or equal to 18 years. We used to evaluate patients the Barthel Index, Karnofsky Performance Scale (KPS), and European Organization for Research in the Treatment of Cancer Questionnaire-core 15 (EORTC-QLQ-C15-PAL). The measurement properties evaluated in this study were test-retest and inter-rater reliability and construct validity (tested by means of correlations with other instruments). RESULTS: We included 220 patients for construct validity and a subsample of 27 patients for reliability analyses. We observed adequate reliability (intraclass correlation coefficient ≥ 0.962) and internal consistency (Cronbach's alpha = 0.942). There were adequate correlations between the Barthel Index and the KPS (rho = 0.766), and the functional capacity domain of the EORTC-QLQ-C15-PAL (rho = -0.698). CONCLUSION: The Brazilian version of the Barthel Index presents adequate test-retest and inter-rater reliability, acceptable internal consistency, and valid construct for measuring functional independence in cancer patients.

Draft Genome Sequence of the Novel, Moderately Thermophilic, Iron- and Sulfur-Oxidizing Firmicute Strain Y002, Isolated from an Extremely Acidic Geothermal Environment.

We report the draft genome sequence of the Firmicute strain Y002, a facultatively anaerobic, acidophilic bacterium that catalyzes the dissimilatory oxidation of iron and sulfur and the reduction of ferric iron. Analysis of the genome (2.9 Mb; G+C content, 46 mol%) provided insights into its ability to grow in extremely acidic geothermal environments.

Composition and functioning of the soil microbiome in the highest altitudes of the Italian Alps and potential effects of climate change.

As the European Alps are experiencing a strong climate warming, this study analyzed the soil microbiome at different altitudes and among different vegetation types at the Stelvio Pass (Italian Alps), aiming to (i) characterize the composition and functional potential of the microbiome of soils and their gene expression during the peak vegetative stage; (ii) explore the potential short-term (using open-top chambers) and long-term (space-for-time substitutions) effects of increasing temperature on the alpine soil microbiome. We found that the functional potential of the soil microbiome and its expression differed among vegetation types. Microbial α-diversity increased along the altitudinal gradient. At lower altitude, shrubland had the highest proportion of fungi, which was correlated with higher amounts of CAZymes, specific for degrading fungal biomass and recalcitrant plant biopolymers. Subalpine upward vegetation shift could lead a possible loss of species of alpine soils. Shrub encroachment may accelerate higher recalcitrant C decomposition and reduce total ecosystem C storage, increasing the efflux of CO2 to the atmosphere with a positive feedback to warming. A total of 5 years of warming had no effect on the composition and functioning of microbial communities, indicating that longer-term warming experiments are needed to investigate the effects of temperature increases on the soil microbiome.

Genetic strategies for improving hyaluronic acid production in recombinant bacterial culture.

Hyaluronic acid (HA) is a biopolymer of repeating units of glucuronic acid and N-acetylglucosamine. Its market was valued at USD 8.9 billion in 2019. Traditionally, HA has been obtained from rooster comb-like animal tissues and fermentative cultures of attenuated pathogenic streptococci. Various attempts have been made to engineer a safe micro-organism for HA synthesis; however, the HA titres obtained from these attempts are in general still lower than those achieved by natural, pathogenic producers. In this scenario, ways to increase HA molecule length and titres in already constructed strains are gaining attention in the last years, but no recent publication has reviewed the main genetic strategies applied to improve HA production on heterologous hosts. In light of that, we hereby compile the advances made in the engineering of micro-organisms to improve HA synthesis.

Alpha-diversity and microbial community structure of the male urinary microbiota depend on urine sampling method.

Considerable variation exists in the methodology of urinary microbiota studies published so far including the cornerstone of any biomedical analysis: sample collection. The aim of this study was to compare the urinary microbiota of first-catch voided urine (FCU), mid-stream voided urine (MSU) and aseptically catheterised urine in men and define the most suitable urine sampling method. Forty-nine men (mean age 71.3 years) undergoing endoscopic urological procedures were enrolled in the study. Each of them contributed three samples: first-catch urine (FCU), mid-stream urine (MSU) and a catheterised urine sample. The samples were subjected to next-generation sequencing (NGS, n = 35) and expanded quantitative urine culture (EQUC, n = 31). Using NGS, Bacteroidetes, Firmicutes, and Proteobacteria were the most abundant phyla in our population. The most abundant genera (in order of relative abundance) included: Prevotella, Veillonella, Streptococcus, Porphyromonas, Campylobacter, Pseudomonas, Staphylococcus, Ezakiella, Escherichia and Dialister. Eighty-two of 105 samples were dominated by a single genus. FCU, MSU and catheterised urine samples differed significantly in three of five alpha-diversity measures (ANOVA, p < 0.05): estimated number of operational taxonomic units, Chao1 and abundance-based coverage estimators. Beta-diversity comparisons using the PIME method (Prevalence Interval for Microbiome Evaluation) resulted in clustering of urine samples according to the mode of sampling. EQUC detected cultivable bacteria in 30/31 (97%) FCU and 27/31 (87%) MSU samples. Only 4/31 (13%) of catheterised urine samples showed bacterial growth. Urine samples obtained by transurethral catheterisation under aseptic conditions seem to differ from spontaneously voided urine samples. Whether the added value of a more exact reflection of the bladder microbiota free from urethral contamination outweighs the invasiveness of urethral catheterisation remains to be determined.

Prokaryotic community diversity during bioremediation of crude oil contaminated oilfield soil: effects of hydrocarbon concentration and salinity.

Crude oil extracted from oilfield reservoirs brings together hypersaline produced water. Failure in pipelines transporting this mixture causes contamination of the soil with oil and hypersaline water. Soil salinization is harmful to biological populations, impairing the biodegradation of contaminants. We simulated the contamination of a soil from an oilfield with produced water containing different concentrations of NaCl and crude oil, in order to evaluate the effect of salinity and hydrocarbon concentration on prokaryote community structure and biodegradation activity. Microcosms were incubated in CO2-measuring respirometer. After the incubation, residual aliphatic hydrocarbons were quantified and were performed 16S rRNA gene sequencing. An increase in CO2 emission and hydrocarbon biodegradation was observed with increasing oil concentration up to 100 g kg-1. Alpha diversity decreased in oil-contaminated soils with an increase in the relative abundance of Actinobacteria and reduction of Bacteroidetes with increasing oil concentration. In the NaCl-contaminated soils, alpha diversity, CO2 emission, and hydrocarbon biodegradation decreased with increasing NaCl concentration. There was an increase in the relative abundance of Firmicutes and Proteobacteria and a reduction of Actinobacteria with increasing salt concentration. Our results highlight the need to adopt specific bioremediation strategies in soils impacted by mixtures of crude oil and hypersaline produced water.

Active Antioxidant Phenolics from Brazilian Red Propolis: An Optimization Study for Their Recovery and Identification by LC-ESI-QTOF-MS/MS.

Brazilian red propolis (BRP) is a natural product widely known for its phenolic composition and strong antioxidant properties. In this study, we used the Box-Behnken Design (BBD) with Surface Response Methodology to optimize the extraction conditions for total phenolic content (TPC) and Trolox equivalent antioxidant capacity(TEAC) of bioactive phenolics from BRP. The extraction time, ethanol/water concentration and temperature, were tested. All variables had significant effects (p ≤ 0.05), with a desirability coefficient of 0.88. Under optimized conditions (90% ethanol at 80 °C for 30 min), the BRP extract showed a TPC of 129.00 ± 2.16 mg GAE/g and a TEAC of 3471.76 ± 53.86 µmol TE/g. Moreover, FRAP and ORAC assays revealed that the optimized BRP extract had 1472.86 ± 72.37 µmol Fe2+/g and 4339.61 ± 114.65 µmol TE/gof dry weight, respectively. Thirty-two phenolic compounds were tentatively identified by LC-QTOF-ESI-MS/MS, of which thirteen were found for the first time in BRP, including four flavones, one flavanol, two flavanones, two chalcones, and four isoflavonoids. Thus, our results highlight the importance of BRP as a source of a wide variety of phenolic compounds with significant antioxidant properties.

Explorative Meta-Analysis of 417 Extant Archaeal Genomes to Predict Their Contribution to the Total Microbiome Functionality.

Revealing the relationship between taxonomy and function in microbiomes is critical to discover their contribution to ecosystem functioning. However, while the relationship between taxonomic and functional diversity in bacteria and fungi is known, this is not the case for archaea. Here, we used a meta-analysis of 417 completely annotated extant and taxonomically unique archaeal genomes to predict the extent of microbiome functionality on Earth contained within archaeal genomes using accumulation curves of all known level 3 functions of KEGG Orthology. We found that intergenome redundancy as functions present in multiple genomes was inversely related to intragenome redundancy as multiple copies of a gene in one genome, implying the tradeoff between additional copies of functionally important genes or a higher number of different genes. A logarithmic model described the relationship between functional diversity and species richness better than both the unsaturated and the saturated model, which suggests a limited total number of archaeal functions in contrast to the sheer unlimited potential of bacteria and fungi. Using the global archaeal species richness estimate of 13,159, the logarithmic model predicted 4164.1 ± 2.9 KEGG level 3 functions. The non-parametric bootstrap estimate yielded a lower bound of 2994 ± 57 KEGG level 3 functions. Our approach not only highlighted similarities in functional redundancy but also the difference in functional potential of archaea compared to other domains of life.

Fungal Communities Are Important Determinants of Bacterial Community Composition in Deadwood.

Fungal-bacterial interactions play a key role in the functioning of many ecosystems. Thus, understanding their interactive dynamics is of central importance for gaining predictive knowledge on ecosystem functioning. However, it is challenging to disentangle the mechanisms behind species associations from observed co-occurrence patterns, and little is known about the directionality of such interactions. Here, we applied joint species distribution modeling to high-throughput sequencing data on co-occurring fungal and bacterial communities in deadwood to ask whether fungal and bacterial co-occurrences result from shared habitat use (i.e., deadwood's properties) or whether there are fungal-bacterial interactive associations after habitat characteristics are taken into account. Moreover, we tested the hypothesis that the interactions are mainly modulated through fungal communities influencing bacterial communities. For that, we quantified how much the predictive power of the joint species distribution models for bacterial and fungal community improved when accounting for the other community. Our results show that fungi and bacteria form tight association networks (i.e., some species pairs co-occur more frequently and other species pairs co-occur less frequently than expected by chance) in deadwood that include common (or opposite) responses to the environment as well as (potentially) biotic interactions. Additionally, we show that information about the fungal occurrences and abundances increased the power to predict the bacterial abundances substantially, whereas information about the bacterial occurrences and abundances increased the power to predict the fungal abundances much less. Our results suggest that fungal communities may mainly affect bacteria in deadwood.IMPORTANCE Understanding the interactive dynamics between fungal and bacterial communities is important to gain predictive knowledge on ecosystem functioning. However, little is known about the mechanisms behind fungal-bacterial associations and the directionality of species interactions. Applying joint species distribution modeling to high-throughput sequencing data on co-occurring fungal-bacterial communities in deadwood, we found evidence that nonrandom fungal-bacterial associations derive from shared habitat use as well as (potentially) biotic interactions. Importantly, the combination of cross-validations and conditional cross-validations helped us to answer the question about the directionality of the biotic interactions, providing evidence that suggests that fungal communities may mainly affect bacteria in deadwood. Our modeling approach may help gain insight into the directionality of interactions between different components of the microbiome in other environments.

16S rRNA Gene Copy Number Normalization Does Not Provide More Reliable Conclusions in Metataxonomic Surveys.

Sequencing 16S rRNA gene amplicons is the gold standard to uncover the composition of prokaryotic communities. The presence of multiple copies of this gene makes the community abundance data distorted and gene copy normalization (GCN) necessary for correction. Even though GCN of 16S data provided a picture closer to the metagenome before, it should also be compared with communities of known composition due to the fact that library preparation is prone to methodological biases. Here, we process 16S rRNA gene amplicon data from eleven simple mock communities with DADA2 and estimate the impact of GCN. In all cases, the mock community composition derived from the 16S sequencing differs from those expected, and GCN fails to improve the classification for most of the analysed communities. Our approach provides empirical evidence that GCN does not improve the 16S target sequencing analyses in real scenarios. We therefore question the use of GCN for metataxonomic surveys until a more comprehensive catalogue of copy numbers becomes available.

Author Correction: GlobalFungi, a global database of fungal occurrences from high-throughput-sequencing metabarcoding studies.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Feeding on fungi: genomic and proteomic analysis of the enzymatic machinery of bacteria decomposing fungal biomass.

Dead fungal biomass is an abundant source of nutrition in both litter and soil of temperate forests largely decomposed by bacteria. Here, we have examined the utilization of dead fungal biomass by the five dominant bacteria isolated from the in situ decomposition of fungal mycelia using a multiOMIC approach. The genomes of the isolates encoded a broad suite of carbohydrate-active enzymes, peptidases and transporters. In the extracellular proteome, only Ewingella americana expressed chitinases while the two Pseudomonas isolates attacked chitin by lytic chitin monooxygenase, deacetylation and deamination. Variovorax sp. expressed enzymes acting on the side-chains of various glucans and the chitin backbone. Surprisingly, despite its genomic potential, Pedobacter sp. did not produce extracellular proteins to decompose fungal mycelia but presumably feeds on simple substrates. The ecological roles of the five individual strains exhibited complementary features for a fast and efficient decomposition of dead fungal biomass by the entire bacterial community.

GlobalFungi, a global database of fungal occurrences from high-throughput-sequencing metabarcoding studies.

Fungi are key players in vital ecosystem services, spanning carbon cycling, decomposition, symbiotic associations with cultivated and wild plants and pathogenicity. The high importance of fungi in ecosystem processes contrasts with the incompleteness of our understanding of the patterns of fungal biogeography and the environmental factors that drive those patterns. To reduce this gap of knowledge, we collected and validated data published on the composition of soil fungal communities in terrestrial environments including soil and plant-associated habitats and made them publicly accessible through a user interface at https://globalfungi.com . The GlobalFungi database contains over 600 million observations of fungal sequences across > 17 000 samples with geographical locations and additional metadata contained in 178 original studies with millions of unique nucleotide sequences (sequence variants) of the fungal internal transcribed spacers (ITS) 1 and 2 representing fungal species and genera. The study represents the most comprehensive atlas of global fungal distribution, and it is framed in such a way that third-party data addition is possible.

Proposal of the CAD System for Melanoma Detection Using Reconfigurable Computing.

This work proposes dedicated hardware to real-time cancer detection using Field-Programmable Gate Arrays (FPGA). The presented hardware combines a Multilayer Perceptron (MLP) Artificial Neural Networks (ANN) with Digital Image Processing (DIP) techniques. The DIP techniques are used to extract the features from the analyzed skin, and the MLP classifies the lesion into melanoma or non-melanoma. The classification results are validated with an open-access database. Finally, analysis regarding execution time, hardware resources usage, and power consumption are performed. The results obtained through this analysis are then compared to an equivalent software implementation embedded in an ARM A9 microprocessor.

Explorative Meta-Analysis of 377 Extant Fungal Genomes Predicted a Total Mycobiome Functionality of 42.4 Million KEGG Functions.

Unveiling the relationship between taxonomy and function of the microbiome is crucial to determine its contribution to ecosystem functioning. However, while there is a considerable amount of information on microbial taxonomic diversity, our understanding of its relationship to functional diversity is still scarce. Here, we used a meta-analysis of completely annotated extant genomes of 377 taxonomically distinct fungal species to predict the total fungal microbiome functionality on Earth with accumulation curves (ACs) of all known functions from the level 3 of KEGG Orthology using both parametric and non-parametric estimates in an explorative data-mining approach. The unsaturated model extrapolating functional diversity as a function of species richness described the ACs significantly better than the saturated model that assumed a limited total number of functions, which suggested the presence of widespread and rare functions. Based on previous estimates of 3.8 million fungal species on Earth, we propagated the unsaturated model to predict a total of 42.4 ± 0.5 million KEGG level 3 functions of which only 0.06% are known today. Our approach not only highlights the presence of widespread and rare functions but points toward the necessity of novel and more sophisticated methods to unveil the entirety of functions to fully understand the involvement of the fungal microbiome in ecosystem functioning.

Database limitations for studying the human gut microbiome.

BACKGROUND: In the last twenty years, new methodologies have made possible the gathering of large amounts of data concerning the genetic information and metabolic functions associated to the human gut microbiome. In spite of that, processing all this data available might not be the simplest of tasks, which could result in an excess of information awaiting proper annotation. This assessment intended on evaluating how well respected databases could describe a mock human gut microbiome. METHODS: In this work, we critically evaluate the output of the cross-reference between the Uniprot Knowledge Base (Uniprot KB) and the Kyoto Encyclopedia of Genes and Genomes Orthologs (KEGG Orthologs) or the evolutionary genealogy of genes: Non-supervised Orthologous groups (EggNOG) databases regarding a list of species that were previously found in the human gut microbiome. RESULTS: From a list which contemplates 131 species and 52 genera, 53 species and 40 genera had corresponding entries for KEGG Database and 82 species and 47 genera had corresponding entries for EggNOG Database. Moreover, we present the KEGG Orthologs (KOs) and EggNOG Orthologs (NOGs) entries associated to the search as their distribution over species and genera and lists of functions that appeared in many species or genera, the "core" functions of the human gut microbiome. We also present the relative abundance of KOs and NOGs throughout phyla and genera. Lastly, we expose a variance found between searches with different arguments on the database entries. Inferring functionality based on cross-referencing UniProt and KEGG or EggNOG can be lackluster due to the low number of annotated species in Uniprot and due to the lower number of functions affiliated to the majority of these species. Additionally, the EggNOG database showed greater performance for a cross-search with Uniprot about a mock human gut microbiome. Notwithstanding, efforts targeting cultivation, single-cell sequencing or the reconstruction of high-quality metagenome-assembled genomes (MAG) and their annotation are needed to allow the use of these databases for inferring functionality in human gut microbiome studies.

The total microbiome functions in bacteria and fungi.

Unveiling the relationship between phylogeny and function of the microbiome is crucial to determine its contribution to ecosystem functioning. However, while there is a considerable amount of information on microbial phylogenetic diversity, our understanding of its relationship to functional diversity is still scarce. Here we predicted the total microbiome functions of bacteria and fungi on Earth using the total known functions from level 3 of KEGG Orthology by modelling the increase of functions with increasing diversity of bacteria or fungi. For bacteria and fungi, the unsaturated model described the data significantly better (for both P <2.2e-16), suggesting the presence of two types of functions. Widespread functions ubiquitous in every living organism that make up two thirds of our current knowledge of microbiome functions are separated from rare functions from specialised enzymes present in only a few species. Given previous estimates on species richness, we predicted a global total of 35.5 million functions in bacteria and 3.2 million in fungi; of which only 0.02% and 0.14% are known today. Our approach highlights the necessity of novel and more sophisticated methods to unveil the entirety of rare functions to fully understand the involvement of the microbiome in ecosystem functioning. SIGNIFICANCE: The functionality of and within a microbial community is generally inferred based on the taxonomic annotation of the organism. However, our understanding of functional diversity and how it relates to taxonomy is still limited. Here we predict the total microbiome functionality in bacteria and fungi on Earth using known and annotated protein-coding sequences in species accumulation curves. Our estimates reveal that the majority of functionality (>99%) could be assigned to yet unknown and rare functions, highlighting that our current knowledge is incomplete and functional inference is thus lackluster.