Metagenomic Profiling Research Articles

A cross-species analysis of fecal microbiomes in humans and mice reveals similarities and dissimilarities associated with prostate cancer risk.

Prostate cancer is a complex disease that develops over time and is influenced by several lifestyle factors that also impact gut microbes. Gut dysbiosis is intricately linked to prostate carcinogenesis, but the precise mechanisms remain poorly understood. Mice are crucial for studying the relationships between gut microbes and prostate cancer, but discovering similarities between humans and mice may aid in elucidating new mechanisms. We used 16s rRNA sequencing data from stool samples of tumor-bearing prostate-specific conditional Pten-knockout mice, disease-free wildtype mice, and a human cohort suspected of having prostate cancer to conduct taxonomic and metagenomic profiling. Features were associated with prostate cancer status and low risk (a negative biopsy of Gleason grade <2) or high risk (Gleason grade ≥2) in humans. In both humans and mice, community composition differed between individuals with and without prostate cancer. Odoribacter spp. and Desulfovibrio spp. were taxa associated with prostate cancer in mice and humans. Metabolic pathways associated with cofactor and vitamin synthesis were common in mouse and human prostate cancer, including bacterial synthesis of folate (vitamin B9), ubiquinone (CoQ10), phylloquinone (vitamin K1), menaquinone (vitamin K2), and tocopherol (vitamin E). Our study provides valuable data that can help bridge the gap between human and mouse microbiomes. Our findings provide evidence to support the notion that certain bacterial-derived metabolites may promote prostate cancer, as well as a preclinical model that can be used to characterize biological mechanisms and develop preventive interventions.

Microbial communities and functions are structured by vertical geochemical zones in a northern peatland

Northern peatlands are important carbon pools; however, differences in the structure and function of microbiomes inhabiting contrasting geochemical zones within these peatlands have rarely been emphasized. Using 16S rRNA gene sequencing, metagenomic profiling, and detailed geochemical analyses, we investigated the taxonomic composition and genetic potential across various geochemical zones of a typical northern peatland profile in the Changbai Mountains region (Northeastern China). Specifically, we focused on elucidating the turnover of organic carbon, sulfur (S), nitrogen (N), and methane (CH4). Three geochemical zones were identified and characterized according to porewater and solid-phase analyses: the redox interface (<10 cm), shallow peat (10–100 cm), and deep peat (>100 cm). The redox interface and upper shallow peat demonstrated a high availability of labile carbon, which decreased toward deeper peat. In deep peat, anaerobic respiration and methanogenesis were likely constrained by thermodynamics, rather than solely driven by available carbon, as the acetate concentrations reached 90 μmol·L−1. Both the microbial community composition and metabolic potentials were significantly different (p < 0.05) among the redox interface, shallow peat, and deep peat. The redox interface demonstrated a close interaction between N, S, and CH4 cycling, mainly driven by Thermodesulfovibrionia, Bradyrhizobium, and Syntrophorhabdia metagenome-assembled genomes (MAGs). The archaeal Bathyarchaeia were indicated to play a significant role in the organic carbon, N, and S cycling in shallow peat. Although constrained by anaerobic respiration and methanogenesis, deep peat exhibited a higher metabolic potential for organic carbon degradation, primarily mediated by Acidobacteriota. In terms of CH4 turnover, subsurface peat (10–20 cm) was a CH4 production hotspot, with a net turnover rate of ∼2.9 nmol·cm−3·d−1, while the acetoclastic, hydrogenotrophic, and methylotrophic methanogenic pathways all potentially contributed to CH4 production. The results of this study improve our understanding of biogeochemical cycles and CH4 turnover along peatland profiles.

Characterization of fungal microbiome structure in leaf litter compost through metagenomic profiling for harnessing the bio-organic fertilizer potential.

The online version contains supplementary material available at 10.1007/s13205-024-04028-0.

Tackling global biogeography and drivers of soil microbial dehalogenation traits and taxa: Insights from metagenomic profiling based on a curated dehalogenase database

To identify microbial resources for dehalogenation, develop effective remediation strategies, and reveal their significance in “One Health”, it is crucial to understand the occurrence, distribution, and drivers of soil dehalogenation functional traits and taxonomy groups at a broad scale, which is currently not well understood. To address the gaps, we characterized the biogeography of both dehalogenation traits and taxa assigned to six dehalogenation pathways, by metagenomic profiling global 4821 soils from eight habitats, based on a manually curated dehalogenase database (DhgaseDB). We found dehalogenation genes and microbes assigned to different pathways are everywhere, but varied consistently across habitats. The similarity of dehalogention traits and taxa composition declines with geographic distance, and that patterns are strongly correlated with geo-environmental factors. We identified anthropogenic organohalide pesticide inputs as the most influential factor on dehalogenation gene abundance, while soil properties, particularly pH, exert a larger impact on dehalogenation taxa diversity. Ultimately, we generated predictive maps of soil dehalogenation gene abundance and taxa diversity for the first time, highlighting the microbial dehalogenation hotpots in East Asia, Australia, Southern Africa, and coastal regions. Collectively, our study highlights the significant role of various microbial dehalogenation processes in organohalide biotransformation and environmental microecology, providing the necessary methodological basis for a deeper comprehension of the underlying mechanisms, thereby contributing to the advancement of tailored strategies for organohalide remediation.

Gut microbiota dysbiosis is associated with altered tryptophan metabolism and dysregulated inflammatory response in COVID-19

The clinical course of COVID-19 is variable and often unpredictable. To test the hypothesis that disease progression and inflammatory responses associate with alterations in the microbiome and metabolome, we analyzed metagenome, metabolome, cytokine, and transcriptome profiles of repeated samples from hospitalized COVID-19 patients and uninfected controls, and leveraged clinical information and post-hoc confounder analysis. Severe COVID-19 was associated with a depletion of beneficial intestinal microbes, whereas oropharyngeal microbiota disturbance was mainly linked to antibiotic use. COVID-19 severity was also associated with enhanced plasma concentrations of kynurenine and reduced levels of several other tryptophan metabolites, lysophosphatidylcholines, and secondary bile acids. Moreover, reduced concentrations of various tryptophan metabolites were associated with depletion of Faecalibacterium, and tryptophan decrease and kynurenine increase were linked to enhanced production of inflammatory cytokines. Collectively, our study identifies correlated microbiome and metabolome alterations as a potential contributor to inflammatory dysregulation in severe COVID-19.

Integrated Metagenomic and Metabolomics Profiling Reveals Key Gut Microbiota and Metabolites Associated with Weaning Stress in Piglets.

(1) Background: Weaning is a challenging and stressful event in the pig's life, which disrupts physiological balance and induces oxidative stress. Microbiota play a significant role during the weaning process in piglets. Therefore, this study aimed to investigate key gut microbiota and metabolites associated with weaning stress in piglets. (2) Methods: A total of ten newborn piglet littermates were randomly assigned to two groups: S (suckling normally) and W (weaned at 21 d; all euthanized at 23 d). Specimens of the cecum were dehydrated with ethanol, cleared with xylene, embedded in paraffin, and cut into 4 mm thick serial sections. After deparaffinization, the sections were stained with hematoxylin and eosin (H&E) for morphometric analysis. Cecal metagenomic and liver LC-MS-based metabolomics were employed in this study. Statistical comparisons were performed by a two-tailed Student's t-test, and p < 0.05 indicated statistical significance. (3) Results: The results showed that weaning led to intestinal morphological damage in piglets. The intestinal villi of suckling piglets were intact, closely arranged in an orderly manner, and finger-shaped, with clear contours of columnar epithelial cells. In contrast, the intestines of weaned piglets showed villous atrophy and shedding, as well as mucosal bleeding. Metagenomics and metabolomics analyses showed significant differences in composition and function between suckling and weaned piglets. The W piglets showed a decrease and increase in the relative abundance of Bacteroidetes and Proteobacteria (p < 0.05), respectively. The core cecal flora in W piglets were Campylobacter and Clostridium, while those in S piglets were Prevotella and Lactobacillus. At the phylum level, the relative abundance of Bacteroidetes significantly decreased (p < 0.05) in weaned piglets, while Proteobacteria significantly increased (p < 0.05). Significant inter-group differences were observed in pathways and glycoside hydrolases in databases, such as the KEGG and CAZymes, including fructose and mannose metabolism, salmonella infection, antifolate resistance, GH135, GH16, GH32, and GH84. We identified 757 differential metabolites between the groups through metabolomic analyses-350 upregulated and 407 downregulated (screened in positive ion mode). In negative ion mode, 541 differential metabolites were identified, with 270 upregulated and 271 downregulated. Major differential metabolites included glycerophospholipids, histidine, nitrogen metabolism, glycine, serine, threonine, β-alanine, and primary bile acid biosynthesis. The significant differences in glycine, serine, and threonine metabolites may be potentially related to dysbiosis caused by weaning stress. Taken together, the identification of microbiome and metabolome signatures of suckling and weaned piglets has paved the way for developing health-promoting nutritional strategies, focusing on enhancing bacterial metabolite production in early life stages.

Gut Microbiome and Osteoarthritis: Insights From the Naturally Occurring Canine Model of Osteoarthritis.

The purpose of this study was to enhance the current knowledge of the relationship between the gut microbiome and osteoarthritis (OA) and associated pain using pet dogs as a clinically relevant translational model. Fecal samples were collected from 93 owned pet dogs. Dogs were designated as either clinically healthy or OA pain using validated methods. Metagenomic profiling was performed through shotgun sequencing using the Illumina NovaSeq platform. MetaPhlAn2 and HUMAnN2 were used to evaluate bacterial taxonomic and pathway relative abundance. Comparisons between healthy and OA-pain groups were performed individually for each taxa using nonparametric tests following Benjamini and Hochberg adjustment for multiple comparisons. Permutation analysis of variance was performed using Bray-Curtis distance matrices. All downstream analyses were completed in R. No significant differences between healthy and OA-pain dogs were observed for alpha and beta diversity. We found 13 taxa with nominally significant (P < 0.05) associations with OA case status, but none of the associations remained significant after adjustment for multiple comparisons. No differences in alpha or beta diversities or the Firmicutes to Bacteroidetes ratio were found regarding pain severity, mobility or activity level, age, or body composition score. Similar to recent studies in humans, the present study did not demonstrate a significant difference in the fecal microbial communities between dogs with OA pain and healthy control dogs. Future research in this naturally occurring model should expand on these data and relate the gut microbiome to gut permeability and circulating proinflammatory and anti-inflammatory molecules to better understand the influence of the gut microbiome on OA and OA pain.

House dust metagenome and pulmonary function in a US farming population

BackgroundChronic exposure to microorganisms inside homes can impact respiratory health. Few studies have used advanced sequencing methods to examine adult respiratory outcomes, especially continuous measures. We aimed to identify metagenomic profiles in house dust related to the quantitative traits of pulmonary function and airway inflammation in adults. Microbial communities, 1264 species (389 genera), in vacuumed bedroom dust from 779 homes in a US cohort were characterized by whole metagenome shotgun sequencing. We examined two overall microbial diversity measures: richness (the number of individual microbial species) and Shannon index (reflecting both richness and relative abundance). To identify specific differentially abundant genera, we applied the Lasso estimator with high-dimensional inference methods, a novel framework for analyzing microbiome data in relation to continuous traits after accounting for all taxa examined together.ResultsPulmonary function measures (forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio) were not associated with overall dust microbial diversity. However, many individual microbial genera were differentially abundant (p-value < 0.05 controlling for all other microbial taxa examined) in relation to FEV1, FVC, or FEV1/FVC. Similarly, fractional exhaled nitric oxide (FeNO), a marker of airway inflammation, was unrelated to overall microbial diversity but associated with differential abundance for many individual genera. Several genera, including Limosilactobacillus, were associated with a pulmonary function measure and FeNO, while others, including Moraxella to FEV1/FVC and Stenotrophomonas to FeNO, were associated with a single trait.ConclusionsUsing state-of-the-art metagenomic sequencing, we identified specific microorganisms in indoor dust related to pulmonary function and airway inflammation. Some were previously associated with respiratory conditions; others were novel, suggesting specific environmental microbial components contribute to various respiratory outcomes. The methods used are applicable to studying microbiome in relation to other continuous outcomes.3hzq1LfdnyTZVYvBm7QT8RVideo

Metagenomic profiling uncovers microbiota and antibiotic resistance patterns across human, chicken, pig fecal, and soil environments

The ongoing and progressive evolution of antibiotic resistance presents escalating challenges for the clinical management and prevention of bacterial infections. Understanding the makeup of resistance genomes and accurately quantifying the current abundance of antibiotic resistance genes (ARGs) are crucial for assessing the threat of antimicrobial resistance (AMR) to public health. This comprehensive study investigated the distribution and diversity of bacterial community composition, ARGs, and virulence factors (VFs) across human, chicken, pig fecal, and soil microbiomes in various provinces of China. As a result, multidrug resistance was identified across all samples. Core ARGs primarily related to multidrug, MLS (Macrolides-Lincosamide-Streptogramins), and tetracycline resistance were characterized. A significant correlation between ARGs and bacterial taxa was observed, especially in soil samples. Probiotic strains such as Lactobacillus harbored ARGs, potentially contributing to the dissemination of antibiotic resistance. We screened subsets of ARGs from samples from different sources as indicators to assess the level of ARGs contamination in samples, with high accuracy. These results underline the complex relationship between microbial communities, resistance mechanisms, and environmental factors, emphasizing the importance of continued research and monitoring to better understand these dynamics.

Investigations of microbiota composition and neuroactive pathways in association with symptoms of stress and depression in a cohort of healthy women.

Despite mounting evidence of gut-brain involvement in psychiatric conditions, functional data remain limited, and analyses of other microbial niches, such as the vaginal microbiota, are lacking in relation to mental health. This aim of this study was to investigate if the connections between the gut microbiome and mental health observed in populations with a clinical diagnosis of mental illness extend to healthy women experiencing stress and depressive symptoms. Additionally, this study examined the functional pathways of the gut microbiota according to the levels of psychological symptoms. Furthermore, the study aimed to explore potential correlations between the vaginal microbiome and mental health parameters in young women without psychiatric diagnoses. In this cross-sectional study, 160 healthy Danish women (aged 18-40 years) filled out questionnaires with validated scales measuring symptoms of stress and depression and frequency of dietary intake. Fecal and vaginal microbiota samples were collected at the beginning of the menstrual cycle and vaginal samples were also collected at cycle day 8-12 and 18-22. Shotgun metagenomic profiling of the gut and vaginal microbiome was performed. The Kyoto Encyclopedia of Genes and Genomes (KEGG) was used for functional profiling and 56 Gut Brain Modules were analyzed in the fecal samples. The relative abundance in the gut of the genera Escherichia, Parabacteroides, and Shigella was higher in women with elevated depressive symptoms. Women with high perceived stress showed a tendency of increased abundance of Escherichia, Shigella, and Blautia. Amongst others, the potentially pathogenic genera, Escherichia and Shigella correlate with alterations in the neuroactive pathways such as the glutamatergic, GABAeric, dopaminergic, and Kynurenine pathways. Vaginosis symptoms were more prevalent in women reporting high levels of stress and depressive symptoms. The findings of this study support the concept of a microbiota-associated effect on the neuroactive pathways even in healthy young women. This suggest, that targeting the gut microbiome could be a promising approach for future psychiatric interventions.

Serum and CSF metabolomics analysis shows Mediterranean Ketogenic Diet mitigates risk factors of Alzheimer’s disease

Alzheimer’s disease (AD) is influenced by a variety of modifiable risk factors, including a person’s dietary habits. While the ketogenic diet (KD) holds promise in reducing metabolic risks and potentially affecting AD progression, only a few studies have explored KD’s metabolic impact, especially on blood and cerebrospinal fluid (CSF). Our study involved participants at risk for AD, either cognitively normal or with mild cognitive impairment. The participants consumed both a modified Mediterranean Ketogenic Diet (MMKD) and the American Heart Association diet (AHAD) for 6 weeks each, separated by a 6-week washout period. We employed nuclear magnetic resonance (NMR)-based metabolomics to profile serum and CSF and metagenomics profiling on fecal samples. While the AHAD induced no notable metabolic changes, MMKD led to significant alterations in both serum and CSF. These changes included improved modifiable risk factors, like increased HDL-C and reduced BMI, reversed serum metabolic disturbances linked to AD such as a microbiome-mediated increase in valine levels, and a reduction in systemic inflammation. Additionally, the MMKD was linked to increased amino acid levels in the CSF, a breakdown of branched-chain amino acids (BCAAs), and decreased valine levels. Importantly, we observed a strong correlation between metabolic changes in the CSF and serum, suggesting a systemic regulation of metabolism. Our findings highlight that MMKD can improve AD-related risk factors, reverse some metabolic disturbances associated with AD, and align metabolic changes across the blood-CSF barrier.

Metagenomic profiling of nasopharyngeal samples from adults with acute respiratory infection.

Diagnosis of acute respiratory infections (ARIs) is challenging due to the broad diversity of potential microbial causes. We used metagenomic next-generation sequencing (mNGS) to analyze the nasopharyngeal virome of ARI patients, who had undergone testing with a clinical multiplex PCR panel (Amplisens ARVI-screen-FRT). We collected nasopharyngeal swabs from 49 outpatient adults, 32 of whom had ARI symptoms and were PCR-positive, and 4 asymptomatic controls in Kazakhstan during Spring 2021. We assessed the biodiversity of the mNGS-derived virome and concordance with PCR results. PCR identified common ARI viruses in 65% of the symptomatic cases. mNGS revealed viral taxa consisting of human, non-human eukaryotic and bacteriophage groups, comprising 15, 11 and 28 genera, respectively. Notable ARI-associated human viruses included rhinovirus (16.3%), betaherpesvirus 7 (14.3%) and Epstein-Barr virus (8.16%). The primary phage hosts were Streptococcus spp. (32.7%), Pseudomonas aeruginosa (24.5%) and Burkholderia spp. (20.4%). In total, 47% of ARIs were linked solely to bacterial pathogens, a third to viral-bacterial co-infections, and less than 10% to only viral infections by mNGS. PCR showed low concordance with mNGS, except for rhinovirus. These results underscore the importance of broad diagnostic methods and question the effectiveness of commonly used PCR panels in ARI diagnosis.

Metagenomic profiling of raw wastewater in Portugal highlights microbiota and resistome signatures of public health interest beyond the usual suspects

In response to the rapid emergence and dissemination of antimicrobial resistant bacteria (ARB) and genes (ARGs), integrated surveillance systems are needed to address antimicrobial resistance (AMR) within the One Health Era. Wastewater analyses enable biomarker monitoring at the sewershed level, offering timely insights into pathogen circulation and ARB/ARGs trends originating from different compartments. During two consecutive epidemic waves of the COVID-19 pandemic in Portugal, taxonomic and functional composition of raw urban wastewater from two wastewater treatment plants (WWTPs) representing one million in equivalent population, located in the main urban areas of the country, were profiled by shotgun metagenomics. Hospital wastewater from two central hospitals located in the WWTPs catchment areas were also sequenced. The resistome and virulome were profiled using metagenomic assemblies without taxonomic constraint, and then specifically characterized for ESKAPE pathogens.Urban and hospital wastewater exhibited specific microbiota signatures, Pseudomonadota dominated in the first and Bacteroidota in the latter. Correlation network analyses highlighted 85 (out of top 100) genera co-occurring across samples. The most frequent ARGs were classified in the multidrug, tetracyclines, and Macrolides, Lincosamides, Streptogramins (MLS) classes. Links established between AMR determinants and bacterial hosts evidenced that the diversity and abundance of ARGs is not restricted to ESKAPE, being also highly predominant among emergent enteropathogens, like Aeromonas and Aliarcobacter, or in the iron (II) oxidizer Acidovorax. The Aliarcobacter genus accumulated high abundance of sulphonamides and polymyxins ARGs, while Acinetobacter and Aeromonas hosted the highest abundance of ARGs against beta-lactams. Other bacteria (e.g. Clostridioides, Francisella, Vibrio cholerae) and genes (e.g. vanA-type vancomycin resistance) of public health interest were detected, with targeted monitoring efforts being needed to establish informative baseline data. Altogether, results highlight that wastewater monitoring is a valuable component of pathogen and AMR surveillance in healthy populations, providing a community-representative snapshot of public health trends beyond priority pathogens.

Strawberry Yield Improvement by Hydrogen-Based Irrigation Is Functionally Linked to Altered Rhizosphere Microbial Communities.

Molecular hydrogen (H2) is crucial for agricultural microbial systems. However, the mechanisms underlying its influence on crop yields is yet to be fully elucidated. This study observed that H2-based irrigation significantly increased strawberry (Fragaria × ananassa Duch.) yield with/without nutrient fertilization. The reduction in soil available nitrogen (N), phosphorus (P), potassium (K), and organic matter was consistent with the increased expression levels of N/P/K-absorption-related genes in root tissues at the fruiting stage. Metagenomics profiling showed the alterations in rhizosphere microbial community composition achieved by H2, particularly under the conditions without fertilizers. These included the enrichment of plant-growth-promoting rhizobacteria, such as Burkholderia, Pseudomonas, and Cupriavidus genera. Rhizobacteria with the capability to oxidize H2 (group 2a [NiFe] hydrogenase) were also enriched. Consistently, genes related to soil carbon (C) fixation (i.e., rbcL, porD, frdAB, etc.), dissimilar nitrate reduction (i.e., napAB and nrfAH), and P solublization, mineralization, and transportation (i.e., ppx-gppA, appA, and ugpABCE) exhibited higher abundance. Contrary tendencies were observed in the soil C degradation and N denitrification genes. Together, these results clearly indicate that microbe-mediated soil C, N, and P cycles might be functionally altered by H2, thus increasing plant nutrient uptake capacity and horticultural crop yield.

Fast and space-efficient taxonomic classification of long reads with hierarchical interleaved XOR filters.

Metagenomic long-read sequencing is gaining popularity for various applications, including pathogen detection and microbiome studies. To analyze the large data created in those studies, software tools need to taxonomically classify the sequenced molecules and estimate the relative abundances of organisms in the sequenced sample. Because of the exponential growth of reference genome databases, the current taxonomic classification methods have large computational requirements. This issue motivated us to develop a new data structure for fast and memory-efficient querying of long reads. Here, we present Taxor as a new tool for long-read metagenomic classification using a hierarchical interleaved XOR filter data structure for indexing and querying large reference genome sets. Taxor implements several k-mer-based approaches, such as syncmers, for pseudoalignment to classify reads and an expectation-maximization algorithm for metagenomic profiling. Our results show that Taxor outperforms state-of-the-art tools regarding precision while having a similar recall for long-read taxonomic classification. Most notably, Taxor reduces the memory requirements and index size by >50% and is among the fastest tools regarding query times. This enables real-time metagenomics analysis with large reference databases on a small laptop in the field.

Marine copepod culture as a potential source of bioplastic-degrading microbiome: The case of poly(butylene succinate-co-adipate)

The poly(butylene succinate-co-adipate) (PBSA) is emerging as environmentally sustainable polyester for applications in marine environment. In this work the capacity of microbiome associated with marine plankton culture to degrade PBSA, was tested. A taxonomic and functional characterization of the microbiome associated with the copepod Acartia tonsa, reared in controlled conditions, was analysed by 16S rDNA metabarcoding, in newly-formed adult stages and after 7 d of incubation. A predictive functional metagenomic profile was inferred for hydrolytic activities involved in bioplastic degradation with a particular focus on PBSA. The copepod-microbiome was also characterized in newly-formed carcasses of A. tonsa, and after 7 and 33 d of incubation in the plankton culture medium. Copepod-microbiome showed hydrolytic activities at all developmental stages of the alive copepods and their carcasses, however, the evenness of the hydrolytic bacterial community significantly increased with the time of incubation in carcasses. Microbial genera, never described in association with copepods: Devosia, Kordia, Lentibacter, Methylotenera, Rheinheimera, Marinagarivorans, Paraglaciecola, Pseudophaeobacter, Gaiella, Streptomyces and Kribbella sps., were retrieved. Kribbella sp. showed carboxylesterase activity and Streptomyces sp. showed carboxylesterase, triacylglycerol lipase and cutinase activities, that might be involved in PBSA degradation. A culturomic approach, adopted to isolate bacterial specimen from carcasses, led to the isolation of the bacterial strain, Vibrio sp. 01 tested for the capacity to promote the hydrolysis of the ester bonds. Granules of PBSA, incubated 82 d at 20 °C with Vibrio sp. 01, were characterized by scanning electron microscopy, infrared spectroscopy, thermogravimetric analysis, and differential scanning calorimetry, showing fractures compared to the control sample, and hydrolysis of ester bonds. These preliminary results are encouraging for further investigation on the ability of the microbiome associated with plankton to biodegrade polyesters, such as PBSA, and increasing knowledge on microorganisms involved in bioplastic degradation in marine environment.

Nutritional attributes and microbial metagenomic profile during solid-state fermentation of soybean meal inoculated with Lactobacillus acidophilus under non-sterile conditions.

Soybean meal (SBM) is used widely in animal feed but it contains anti-nutritional factors (ANFs) such as protease inhibitors - immunogenic proteins that limit its utilization. Fermentative processes could help to reduce these ANFs. The aim of this study was to evaluate the nutritional attributes, bacterial community dynamics, and microbial metagenomic profile during the solid-state fermentation of SBM using a strain of the bacterium Lactobacillus acidophilus with or without pre-autoclaving treatment. Following fermentation, there was a reduction in the pH and a concurrent increase in the population of lactic acid bacteria. Fermentation also resulted in an increase in both crude and soluble protein levels. Trypsin inhibitor levels decreased after fermentation, particularly in fermented SBM that had not been pre-autoclaved, with an inactivation rate higher than 90%. Moreover, high-molecular-weight peptides (44-158 kDa), specifically some polypeptides from the soybean immunogen glycinin and β-conglycinin, underwent degradation during the fermentation process. Bacterial community analysis revealed the dominance of the Lactobacillus genus in all samples, regardless of the treatments applied. Metagenomic profiling identified L. acidophilus as the dominant species in inoculated SBM, irrespective of whether pre-autoclaving was conducted or not. This study demonstrates the feasibility of solid-state fermentation with L. acidophilus under non-sterile conditions to inactivate trypsin inhibitor and increase protein concentration and hydrolysate immunogen proteins into low-molecular-weight peptides in SBM. Lactobacillus acidophilus inoculum also inhibited the growth of undesirable bacteria. This knowledge contributes to our understanding of the potential applications of solid-state fermentation with L. acidophilus in improving the nutritional quality of SBM. © 2024 Society of Chemical Industry.

Preventive effect of prenatal maternal oral probiotic supplementation on neonatal jaundice (POPS Study): A protocol for the randomised double-blind placebo-controlled clinical trial

IntroductionNeonatal jaundice is a common and life-threatening health problem in neonates due to overaccumulation of circulating unconjugated bilirubin. Gut flora has a potential influence on bilirubin metabolism. The infant gut...

Tracing the origin and authenticity of Spanish PDO honey using metagenomics and machine learning

The Protected Designation of Origin (PDO) indication for foods intends to guarantee the conditions of production and the geographical origin of regional products within the European Union. Honey products are widely consumed due to their health-promoting properties and there is a general interest in tracing their authenticity. In this regard, metagenomics sequencing and machine learning (ML) have been proposed as complementary technologies to improve the traceability methods of foods. Therefore, the aim of this study was to analyze the metagenomic profiles of Spanish honeys from three different PDOs (Granada, Tenerife and Villuercas-Ibores), and compare them with non-PDO honeys using ML models (PLS, RF, LOGITBOOST, and NNET). According to the results obtained, non-PDO honeys and Granada PDO showed higher beta diversity values than Tenerife and Villuercas-Ibores PDOs. ML classification of honey products allowed the identification of different microbial biomarkers of the geographical origin of honeys: Lactobacillus kunkeei, Parasaccharibacter apium and Lactobacillus helsingborgensis for PDO honeys and Paenibacillus larvae, Lactobacillus apinorum and Klebsiella pneumoniae for non-PDO honeys. In addition, potential microbial biomarkers of some honey varieties including L. kunkeei for Albaida and Retama del Teide varieties, and P. apium for Tajinaste variety, were identified. ML models were validated on an independent set of samples leading to high accuracy rates (above 90 %). This work demonstrates the potential of ML to differentiate different types of honey using metagenome-based methods, leading to high performance metrics. In addition, ML models discriminate both the geographical origin and variety of products corresponding to different PDOs and non-PDO products. Results here presented may contribute to develop enhanced traceability and authenticity methods that could be applied to a wide range of foods.

Novel screening approach for cancer cachexia using metagenomic gut microbiome profiling in patients with advanced non-small cell lung cancer.

12090 Background: Cancer cachexia (CC) is a multifactorial syndrome involving immune-metabolic crosstalk across multiple organs and has been associated with a negative clinical impact in patients with non-small cell lung cancer (NSCLC) amenable to immune checkpoint inhibitors (ICIs). In parallel, the gut microbiome (GM) has emerged as a key contributor to ICI response. In this study, we aimed to evaluate the association between CC and GM composition and its metabolic potentials. Methods: We collected fecal samples from 139 patients with advanced NSCLC treated with ICI. In addition to 16S rRNA sequencing for all patients, shotgun metagenomic microbiome profiling was performed for 69 patients to estimate the species-level composition and functional capacity of the GM. Cancer cachexia was diagnosed according to the international consensus based on the body weight changes over the previous six months. Survival time was calculated using the Kaplan-Meier method. GM diversity indices, differential abundance, and functional profiles based on the MetaCyc database were compared between the patients with and without CC. Results: Median progression-free survival (PFS) and overall survival (OS) were significantly shorter in the cachexia group compared to the non-cachexia group [4.5 vs. 11.5 months (p &lt; 0.001) and 10.8 vs. 44.9 months (p &lt; 0.01), respectively]. Both GM profiling techniques revealed a significant difference in beta diversity between both groups (p &lt; 0.01). In addition, metagenomic analyses revealed the distinct characteristics of GM at the species level between the groups. The CC group showed an overrepresentation of the commensal bacteria, such as Escherichia coli, Ruthenibacterium lactatiformans, Hungatella hathewayi,and Eggerthella lenta, whereas the non-CC group showed an enrichment of Parabacteroides distasonis, Eubacterium rectale,and Roseburia inulinivorans. Moreover, functional analysis revealed the significantly different metabolic potentials of GM in the CC group. The CC group showed an enrichment of pathways, such as D-arabinose degradation II, L-lysine degradation, and octan oxidation. Finally, the clustering of patients based on significant metabolic pathways or gene reactions provided a high predictive ability to discriminate between patients with and without CC. Conclusions: The shotgun metagenomic approach allowed for the characterization of the altered gut microbes and their metabolic potentials in patients with CC. Stratification based on the GM profiles may be useful as a novel screening method for CC, which is progressive and may involve more multistage pathology than identified by the conventional approach.