Bracken: estimating species abundance in metagenomics data

The stems and leaves of Panax notoginseng reduce the abundance of antibiotic resistance genes by regulating intestinal microbiota in Duzang pigs

In order to study the distribution characteristics of intestinal microbiota and antibiotic resistance genes (ARGs) in Duzang pigs after adding stems and leaves of Panax notoginseng to the feed, the characteristics of intestinal microbiota were explored by metagenomic sequencing, and 14 ARGs and 2 integrase genes were detected by qPCR. The results showed that the addition of stems and leaves of P. notoginseng increased the relative abundance of Firmicutes, Lactobacillus and Pediococcus in the cecum of Duzang pigs. A total of 10 ARGs and 2 integrase genes were detected in the cecal contents of pigs. The addition of stems and leaves of P. notoginseng reduced the relative abundance of total ARGs, ermB, tetO and tetW in the cecum of Duzang pigs. The results of network analysis showed that multiple genera were potential hosts of ARGs. The addition of stems and leaves of P. notoginseng may reduce the relative abundance of ARGs by reducing the relative abundance of genera such as Corynebacterium and Flavonifractor, thereby reducing the risk of ARGs spread. This study provides a theoretical basis for the rational use of stems and leaves of P. notoginseng to control ARGs.

Best practices for developing microbiome-based disease diagnostic classifiers through machine learning

The human gut microbiome, crucial in various diseases, can be utilized to develop diagnostic models through machine learning (ML). The specific tools and parameters used in model construction such as data preprocessing, batch effect removal and modeling algorithms can impact model performance and generalizability. To establish an generally applicable workflow, we divided the ML process into three above-mentioned steps and optimized each sequentially using 83 gut microbiome cohorts across 20 diseases. We tested a total of 156 tool-parameter-algorithm combinations and benchmarked them according to internal- and external- AUCs. At the data preprocessing step, we identified four data preprocessing methods that performed well for regression-type algorithms and one method that excelled for non-regression-type algorithms. At the batch effect removal step, we identified the "ComBat" function from the sva R package as an effective batch effect removal method and compared the performance of various algorithms. Finally, at the ML algorithm selection step, we found that Ridge and Random Forest ranked the best. Our optimized work flow performed similarly comparing with previous exhaustive methods for disease-specific optimizations, thus is generally applicable and can provide a comprehensive guideline for constructing diagnostic models for a range of diseases, potentially serving as a powerful tool for future medical diagnostics.

Metabolic responses of microalgal-bacterial granular sludge to enrofloxacin and sulfamethoxazole exposure

This study examined the removal performance and responses of the microalgal-bacterial granular sludge (MBGS) system to enrofloxacin (ENR), sulfamethoxazole (SMX), and their combination. Results showed that MBGS could achieve 73.2 % and 64.0 % removals of ENR and SMX at 1 mg/L of mixed antibiotics, while ENR severely affected organics removal (from 84.5 % to 74.7 %). Antibiotic exposures could raise reactive oxygen species levels, thereby disrupted cellular structures and energy metabolism. ENR had the most significant disruptive effect, markedly reducing the abundance of Oscillatoriales and impairing their interactions with other taxa. In contrast, Xanthomonadales and Micrococcales were essential for sustaining energy metabolism under ENR stress, while Hyphomicrobiales demonstrated strong adaptability to these antibiotics. Notably, the combination of ENR and SMX mitigated oxidative stress, facilitating the growth of Rhodospirillales and Chloroflexales. These findings provide insights into microbial adaptation mechanisms under antibiotic pressure and offer guidance for optimizing wastewater treatment strategies in antibiotic-contaminated environments.

Marine steel protection based on biomineralization for sustainable development of coastal cities

Corrosion research, spanning over 150 years, remains critically important, particularly for addressing marine microbially induced corrosion on steel, which causes significant economic losses and safety risks. This study proposes a biomineralization method using marine urease-producing bacteria to protect steel. Urease-producing bacteria were enriched to promote biomineralization, and a seawater corrosion experiment was conducted to evaluate its efficacy. Results showed that biomineralization significantly reduced corrosion rates, especially with yeast extract enrichment, and decreased the abundance of sulfate-reducing bacteria and sulfur-oxidizing bacteria in biofilms. Functional gene analysis identified Thioalkalivibrio as a key indicator of sulfate reduction. The findings demonstrated that the formed biomineralized film acted as a protective layer to isolate the steel from the corrosive seawater, which contributed to the advancement of novel techniques for corrosion inhibition of marine steel to achieve long-term sustainability for ships and engineering structures.

Metagenomics-based tracing of genetically modified microorganism contaminations in commercial fermentation products

Genetically modified microorganisms (GMM) are frequently employed for the production of microbial fermentation products such as food enzymes. Although presence of the GMM or its recombinant DNA in the final product is not authorized, contaminations occur frequently. Insight into the contamination source of a GMM is of crucial importance to allow the competent authorities to take appropriate action. The aim of this study was to explore the feasibility of a metagenomic shotgun sequencing approach to investigate microbial contamination in fermentation products, focusing on source tracing of GMM strains using innovative strain deconvolution and phylogenomic approaches. In most cases, analysis of 16 GMM-contaminated food enzyme products supported finding the same GM producer strains in different products, while often multiple GMM contaminations per product were detected. Presence of AMR genes in the samples was strongly associated with GMM contamination, emphasizing the potential public health risk. Additionally, a variety of other microbial contaminations were detected, identifying a group of samples with a conspicuously similar contamination profile, which suggested that these samples originated from the same production facility or batch. Together, these findings highlight the need for guidelines and quality control for traceability of these products to ensure the safety of consumers. This study demonstrates the added value of metagenomics to obtain insight in the microbial contamination profiles, as well as their underlying relationships, in commercial microbial fermentation products. The proposed approach may be applied to other types of microbial fermentation products and/or to other (genetically modified) producer strains.

Comprehensive assessment of antibiotic impacts and risk thresholds on aquatic microbiomes and resistomes

Understanding the impacts of environmentally relevant low-level antibiotics on aquatic microbiomes and resistomes is crucial for risk assessment of anthropogenic antibiotic contamination. Here, we investigated the effects of seven subinhibitory concentrations of trimethoprim and lincomycin (10 ng/L to 10 mg/L), individually and in combination, on surface water microcosms over 1 and 7 days, using unspiked samples as controls. Metagenomic sequencing revealed a decrease in bacterial community α-diversity and an increase in resistome α-diversity with rising antibiotic concentrations upon 7 days of exposure. Notably, the β-diversity of both bacterial communities and resistomes exhibited a biphasic response, decreasing and then increasing with breakpoint concentrations of 2.73 µg/L and 0.68 µg/L, respectively. We also observed concentration-dependent increases in certain metagenome-assembled antibiotic-resistant bacteria (MAARB) and antibiotic resistance genes (ARGs), with minimum selective concentrations (MSCs) of 2.28 µg/L for trimethoprim targeting OXA-21 and 32.4 µg/L for lincomycin targeting erm(F). Among various metrics for identifying risk thresholds that induce significant changes in microbial taxa, resistomes, individual ARGs, and MAARB, the breakpoint concentration derived from resistome β-diversity was the most conservative. We propose integrating this metric into environmental risk assessment frameworks for antibiotics. Our study provides a systematic evaluation of antibiotic impacts on aquatic microbiomes and resistomes, offering key insights for refining risk assessments of antibiotic contamination in aquatic environments.

The use of metagenomics to enhance diagnosis of encephalitis

INTRODUCTION

Encephalitis has a broad etiology, including infectious and auto-immune causes. In infectious encephalitis, the breadth of causative organisms results in incomplete testing and low diagnostic yields.Metagenomics sequences all DNA and RNA allowing untargeted detection of all organisms in a single specimen; this is of particular use in diagnosis of encephalitis with a broad etiology.

AREAS COVERED

We review the literature and discuss metagenomics workflows, host depletion and pathogen enrichment methods, bioinformatics analysis and potential analysis of the host transcriptome to aid diagnosis. We discuss the clinical use of metagenomics for diagnosis of neurological infection including time to result, cost, quality assurance, patient cohorts in whom metagenomics adds the most value, recommended specimen types, limitations and review published cases in which metagenomics has been used to diagnose encephalitis.

EXPERT OPINION

There is good evidence for the utility of metagenomics to diagnose infection in encephalitis. Due to infections with rare, unexpected or novel pathogens, metagenomics adds most value to diagnosis in immunocompromised patients and the greatest diagnostic yield is in brain biopsies. Technical advances are needed to reduce the complexity, cost and time to result which will enable wider adoption in clinical laboratories and use as a first-line test.

Exposure and health risks of livestock air resistomes

Most of the global antibiotic consumption is by the livestock industry, making livestock farms a hotspot of antibiotic resistance genes (ARGs). Farm air poses direct ARG exposure to workers, but the health risks of air resistomes remain unclear. We evaluated the human exposure and health risks of air resistomes in pig and chicken farms and compared air resistomes in Chinese farms to those in European farms given their long-term restrictions on use of antibiotics in livestock. We found that livestock air was highly enriched in ARGs, with each cell harboring seven times more ARGs than urban air. The daily ARG inhalation of farm workers was equivalent to several years of ARG inhalation by urban residents. ARGs encoding resistance to last-resort antibiotics such as mcr-1 and tetX were detected in farm air, and tetX variants were prevalent in both Chinese and European farms. ARGs in livestock air were highly associated with mobile genetic elements, and conjugation experiments confirmed their cross-phyla transferability. The projected resistome risk of farm air was significantly higher than well-recognized ARG hotspots like air from hospitals, sewage treatment plants, and from animal manures. The diversity, abundance, and risk score of air resistomes in Chinese farms were significantly higher than those in European farms, suggesting that long-term restriction of antibiotic use mitigates antibiotic resistance in the livestock environment. Our results underscore the high exposure of farm workers to ARGs via farm air and highlight its role in ARG dissemination, supporting the importance of antibiotic stewardship practices in combating antibiotic resistance.

Potential of lavender essential oil to inhibit tetracycline resistance and modulate gut microbiota in black soldier fly larvae

The misuse of tetracycline in livestock farming leads to environmental residues that promote the proliferation of antibiotic resistance genes (ARGs), particularly tetracycline resistance (tet) genes. Black soldier fly (BSF) larvae, used for organic waste bioconversion, may carry tetracycline residues in their guts, raising concerns about ARG spread. To address this issue, plant-derived additives such as lavender essential oil (LEO) have been explored as alternative antibiotics. This study investigated the effects of LEO on tet gene suppression and gut microbiota modulation in BSF larvae. Results showed that oxytetracycline treatment increased tet gene relative abundance threefold compared to the control, reaching 1.13 ± 0.29 and enriched pathogens Klebsiella oxytoca and Enterobacter hormaechei. Conversely, LEO treatment (100 mg/kg) reduced tet gene abundance by 46.67 %, from 0.15 ± 0.02 to 0.08 ± 0.02, and enhanced beneficial microorganisms like Leuconostoc pseudomesenteroides. Furthermore, LEO reduced tet gene relative abundance in oxytetracycline-treated larvae from 1.13 ± 0.29 to 0.49 ± 0.19 and 0.70 ± 0.11 in separate treatments. LEO modified fungal composition and nutrient pathways. Network analysis revealed that LEO promoted a more integrated and modular gut microbiota, enhancing functional specialization and resilience. These findings suggest LEO can mitigate ARGs in BSF larvae, offering a sustainable approach for antibiotic resistance management in organic waste recycling and livestock farming.

Longitudinal profiling of low-abundance strains in microbiomes with ChronoStrain

The ability to detect and quantify microbiota over time from shotgun metagenomic data has a plethora of clinical, basic science and public health applications. Given these applications, and the observation that pathogens and other taxa of interest can reside at low relative abundance, there is a critical need for algorithms that accurately profile low-abundance microbial taxa with strain-level resolution. Here we present ChronoStrain: a sequence quality- and time-aware Bayesian model for profiling strains in longitudinal samples. ChronoStrain explicitly models the presence or absence of each strain and produces a probability distribution over abundance trajectories for each strain. Using synthetic and semi-synthetic data, we demonstrate how ChronoStrain outperforms existing methods in abundance estimation and presence/absence prediction. Applying ChronoStrain to two human microbiome datasets demonstrated its improved interpretability for profiling Escherichia coli strain blooms in longitudinal faecal samples from adult women with recurring urinary tract infections, and its improved accuracy for detecting Enterococcus faecalis strains in infant faecal samples. Compared with state-of-the-art methods, ChronoStrain's ability to detect low-abundance taxa is particularly stark.

Metagenomic insights into cyanotoxin dynamics in a Mexican subtropical lake

Valle de Bravo is a vital water supply for part of the metropolitan area of the Valle de Mexico megacity, providing 30% of Mexico City's water demand. This water body has experienced an acceleration in its trophic status, going from oligotrophic to eutrophic in just a few years. This temperate lake (at a tropical latitude) is in a persistent bloom dominated by a variety of co-occurring cyanobacteria, many of which have toxigenic potential based on microscopic identification, that makes it difficult or even impractical to identify the cyanotoxin producers. To unravel this complexity and directly identify the toxigenic genera, we showed that integrating classical approaches with metagenomic is required. We first characterized, from genes to metagenomes assembled genomes, the toxigenic Cyanobacteria. We found that Microcystis was the most dominant cyanobacterial genus and the sole carrier of the mcy operon, making it the only microcystin producer. We then quantified twenty-one different cyanopeptides, including twelve microcystin congeners using a high-performance liquid chromatography-high-resolution. Nine microcystins (MCs) and the emerging cyanotoxin anabaenopeptin-A and -B were found at varying concentrations throughout the year, with MC-LA being the most common and abundant. Our findings, constrained by our sampling strategy, indicate that conventional cyanotoxin biomarkers (e.g., toxin mcy genes) were not consistently reliable indicators of cyanotoxin concentrations in this freshwater system. In this study, we followed the dynamics of the cyanobacterial community and the associated cyanopeptides with unprecedented resolution. Our results have implications for better management of toxic blooms in this freshwater system, which supplies drinking water to more than 7 million people in the megalopolis of Valle de México.

Microbial diversity of the remote Trindade Island, Brazil: a systematic review

Trindade Island is a unique volcanic environment in the South Atlantic, characterized by acidic soils, rich organic matter and a high diversity of micro- and macroorganisms. Such diversity can represent a range of ecological niches and functions, potentially offering valuable ecosystem services. This systematic review aimed to synthesize the current knowledge of the island's microbial communities, focusing on their ecological roles and biotechnological potential. Following the PRISMA guidelines, a comprehensive search of the scientific literature was conducted to identify studies that performed DNA sequencing of samples collected on Trindade Island, Brazil. The selected studies used approaches, such as shotgun metagenomics and marker gene sequencing, including samples from microcosm experiments and culture-dependent samples. A total of eight studies were selected, but only six provided detailed taxonomic information, from which more than 850 genera of Bacteria, Archaea, and Fungi were catalogued. Soil communities were dominated by Actinobacteriota, Acidobacteriota, and Ascomycota (Fungi) while marine and coral environments showed high diversity of Pseudomonadota and Cyanobacteria. Microcosm experiments revealed adaptive responses to hydrocarbon contamination, mainly for Alcanivorax and Mortierella (Fungi). Compared to other ecosystems, such as the oligotrophic Galapagos Islands and the sea-restricted Cuatro Cienegas Basin, Cyanobacteria were shown to be more adaptive.

Urban wild bee well-being revealed by gut metagenome data: A mason bee model

Wild bees are ecologically vital but increasingly threatened by anthropogenic activities, leading to uncertain survival and health outcomes in urban environments. The gut microbiome contains features indicating host health and reflecting long-term evolutionary adaptation and acute reactions to real-time stressors. Moving beyond bacteria, we propose a comprehensive analysis integrating diet, bacteriome, virome, resistome, and their association to understand the survival status of urban lives better. We conducted a study on mason bees (Osmia excavata) across 10 urban agricultural sites in Suzhou, China, using shotgun gut metagenome sequencing for data derived from total gut DNA. Our findings revealed that most ingested pollen originated from Brassica crops and the unexpected garden tree Plantanus, indicating that floral resources at the 10 sites supported Osmia but with limited plant diversity. Varied city landscapes revealed site-specific flowers that all contributed to Osmia sustenance. The gut bacterial community, dominated by Gammaproteobacteria, showed remarkable structural stability across 8 sites but suggested perturbations at 2 sites. Antibiotic resistance gene profiles highly varied across 10 sites with prevalent unclassified drug classes, highlighting environmental threats to both bees and humans. The virome analysis identified honeybee pathogens, suggesting potential virus spillover. Many unknown bacteriophages were detected, some of which targeted the core gut bacteria, underscoring their role in maintaining gut homeostasis. These multifaceted metagenomic insights hold the potential to predict bee health and identify environmental threats, thereby guiding probiotic development and city management for effective bee conservation.

Host-specific microbiome-rumination interactions shape methane-yield phenotypes in dairy cattle

Enteric methane emissions (EMEs) negatively impact both the environment and livestock efficiency. Given the proposed link between CH4 yield and the rumination time (RT) phenotype, we hypothesize that this connection is mediated by the gut microbiome. This study investigated the RT-microbiome-EME connection using rumination-bolus, fecal, and rumen microbiomes as non-invasive proxies for identifying low-EME cows. High-RT cows ruminated 94 minutes longer per day (20%) and exhibited 26% lower EME than low-RT cows, confirming a strong RT-CH4-yield association. Microbial analysis revealed conserved methanogen diversity across the rumen, bolus, and fecal microbiomes, though functional differences were evident. High-RT cows had a greater abundance of Methanosphaera stadtmanae, suggesting an increased potential for methylotrophic methanogenesis, whereas low-RT cows exhibited higher Methanobrevibacter YE315 abundance, indicative of CO2-utilizing methanogenesis. Additionally, high-RT cows showed increased alternative hydrogen sinks, supported by upregulated genes encoding fumarate reductase, sulfate reductase, nitrate reductase, and ammonia-forming nitrite reductase, thereby reducing hydrogen availability for methanogenesis. Metabolically, high-RT cows had higher propionate concentrations and were enriched with rapid-fermenting bacteria (Prevotella, Sharpea, Veillonellaceae, and Succinivibrionaceae), whereas low-RT cows exhibited higher acetate concentrations with elevated acetate-producing pathways, reflecting differences in energy partitioning mechanisms. This study establishes RT as a microbiome-linked, non-invasive screening tool for identifying low-EME cows. The observed microbial and metabolic shifts in high-RT cows suggest that RT-based selection could enhance methane mitigation, rumen efficiency, and climate-smart livestock production. Leveraging RT-associated microbial profiles offers a scalable and cost-effective approach to reducing EME in cattle.

IMPORTANCE

Methane emissions from livestock contribute to climate change and reduce animal efficiency. This study reveals that cows with longer rumination times (chewing cud for an extra 94 minutes daily) produce 26% less methane than cows with shorter rumination times. The gut microbiome plays a key role-low-methane cows host microbial communities that produce less methane while efficiently utilizing hydrogen for energy conservation in the rumen. By analyzing rumination sensor data and/or in combination with microbial profiles from rumen or fecal samples, farmers can non-invasively identify and select cows that naturally emit less methane. This scalable, cost-effective strategy offers a practical solution for reducing livestock's environmental footprint while enhancing efficiency and advancing climate-smart agriculture.

Intraspecies dynamics underlie the apparent stability of two important skin microbiome species

Adult human facial skin microbiomes are remarkably similar at the species level, dominated by Cutibacterium acnes and Staphylococcus epidermidis, yet each person harbors a unique community of strains. Understanding how person-specific communities assemble is critical for designing microbiome-based therapies. Here, using 4,055 isolate genomes and 356 metagenomes, we reconstruct on-person evolutionary history to reveal on- and between-person strain dynamics. We find that multiple cells are typically involved in transmission, indicating ample opportunity for migration. Despite this accessibility, family members share only some of their strains. S. epidermidis communities are dynamic, with each strain persisting for an average of only 2 years. C. acnes strains are more stable and have a higher colonization rate during the transition to an adult facial skin microbiome, suggesting this window could facilitate engraftment of therapeutic strains. These previously undetectable dynamics may influence the design of microbiome therapeutics and motivate the study of their effects on hosts.

AI for rapid identification of major butyrate-producing bacteria in rhesus macaques (Macaca mulatta)

BACKGROUND

The gut microbiome plays a crucial role in health and disease, influencing digestion, metabolism, and immune function. Traditional microbiome analysis methods are often expensive, time-consuming, and require specialized expertise, limiting their practical application in clinical settings. Evolving artificial intelligence (AI) technologies present opportunities for developing alternative methods. However, the lack of transparency in these technologies limits the ability of clinicians to incorporate AI-driven diagnostic tools into their healthcare systems. The aim of this study was to investigate an AI approach that rapidly predicts different bacterial genera and bacterial groups, specifically butyrate producers, from digital images of fecal smears of rhesus macaques (Macaca mulatta). In addition, to improve transparency, we employed explainability analysis to uncover the image features influencing the model's predictions.

RESULTS

By integrating fecal image data with corresponding metagenomic sequencing information, the deep learning (DL) and machine learning (ML) algorithms successfully predicted 16 individual bacterial genera (area under the curve (AUC) > 0.7) among the 50 most abundant genera in rhesus macaques (Macaca mulatta). The model was successful in predicting functional groups, major butyrate producers (AUC 0.75) and a mixed group including fermenters and short-chain fatty acid (SCFA) producers (AUC 0.81). For both models of butyrate producers and mixed fermenters, the explainability experiments revealed no decline in the AUC when random noise was added to the images. Increased blurring led to a gradual decline in the AUC. The model's performance was robust against the impact of fecal shape from smearing, with a stable AUC maintained until patch 4 for all groups, as assessed through scrambling. No significant correlation was detected between the prediction probabilities and the total fecal weight used in the smear; r = 0.30 ± 0.3 (p > 0.1) and r = 0.04 ± 0.36 (p > 0.8) for the butyrate producers and mixed fermenters, respectively.

CONCLUSION

Our approach demonstrated the ability to predict a wide range of clinically relevant microbial genera and microbial groups in the gut microbiome based on digital images from a fecal smear. The models proved to be robust to the smearing method, random noise and the amount of fecal matter. This study introduces a rapid, non-invasive, and cost-effective method for microbiome profiling, with potential applications in veterinary diagnostics.

The impact of anthropogenic activities on antimicrobial and heavy metal resistance in aquatic environments

This study investigated the prevalence and co-occurrence of antimicrobial (AMR) and metal resistance (MR) in aquatic environments with different human impacts. Metagenomes from pristine, rural and urban sites in Australia were analyzed with AMR ++ and customized binning pipelines. AMR was present in all environments, while MR was mainly in rural and urban samples. AMR gene diversity was higher in rural and urban sites, exhibiting resistance to more antibiotic classes (n = 10) than the pristine site (n = 4). Metal and multicompound resistance was more frequent in rural (14%) compared to urban samples (5%). Pristine samples lacked multidrug and multicompound resistance and had lower resistance to aminoglycosides and the MLS group. Multiresistance was evidenced by copper and aminocoumarin resistance in rural samples and aminoglycoside and mercury resistance in Pseudomonas in all environments. These findings highlight the impact of human activities on AMR and MR spread, emphasizing the need for environmental monitoring and management.

IMPORTANCE

Antimicrobial resistance (AMR) and metal resistance (MR) are critical global health concerns exacerbated by anthropogenic activities. The intricate mechanism underlying the interaction among anthropogenic activities, microbial communities, and resistance remains enigmatic. We developed novel bioinformatic pipelines to unveil this interaction in three aquatic environments. Our findings demonstrate the presence of specific bacterial communities that drive AMR and MR in rural and urban environments. This study underscores the significance of proper agricultural practices, comprehensive monitoring, and management strategies to reduce anthropogenic impacts on environmental resistance.

Genomic Identification and Characterization of Saxitoxin Producing Cyanobacteria in Western Lake Erie Harmful Algal Blooms

Saxitoxins (STXs), a group of closely related neurotoxins, are among the most potent natural toxins known. While genes encoding STX biosynthesis have been observed in Lake Erie, the organism(s) responsible for producing STXs in the Laurentian Great Lakes have not been identified. We identified a full suite of STX biosynthesis genes in a Dolichospermum metagenome-assembled genome (MAG). The content of sxt genes suggest that this organism can produce STX, decarbamoyl and deoxy-decarbamoyl saxitoxins, and other congeners. The absence of sxtX indicates this organism is unable to produce neosaxitoxin, a potent congener. However, a distinct, lower abundance sxt operon from an unidentified organism did contain sxtX, indicating neosaxitoxin biosynthesis potential. Metatranscriptomic data confirmed STX biosynthesis gene expression. We also recovered highly similar Dolichospermum MAGs lacking sxt genes, implying gene loss or horizontal gene transfer. sxtA was detected by quantitative polymerase chain reaction during 47 of 76 sampling dates between 2015 and 2019, demonstrating higher sensitivity than metagenomic approaches. sxtA gene abundance was positively correlated with temperature and particulate nitrogen:phosphorus ratio and negatively correlated with ammonium concentration. All Dolichospermum MAGs had genes required for nitrogen fixation. Collectively, this study provides a foundation for understanding potential new threats to Lake Erie water quality.

Optimizing anti-PD-1/PD-L1 therapy efficacy and fecal microbiota transplantation donor selection through gut mycobiome-based enterotype

Immunotherapy has revolutionized cancer treatment, but response variability remains a challenge. The gut microbiome's role in therapeutic efficacy is well established, but the impact of the gut mycobiome is less understood. Using unsupervised clustering, we identify two gut mycobiome-based enterotypes, favorable type and unfavorable type, characterized by distinct microbial compositions linked to immunotherapy outcomes. Favorable-type enterotypes exhibit higher fungal and bacterial alpha diversity, enriched butyrate-producing bacteria, and metabolic pathways related to butyric acid and sugar/starch metabolism. External validation confirms their predictive value in assessing immunotherapy efficacy. Multi-omics analysis reveals increased CD8+ T cell infiltration in the tumor microenvironment of favorable-type patients. Fecal microbiota transplantation (FMT) from favorable-type donors enhances anti-PD-1 sensitivity, promotes CD8+ T cell infiltration, and boosts butyrate production in vivo. These findings highlight the gut mycobiome's role in immunotherapy response and support FMT from favorable-type donors as a potential strategy for improving treatment outcomes and patient stratification.

Relationship Between Dietary Habits and Stress Responses Exerted by Different Gut Microbiota

BACKGROUND/OBJECTIVES

A number of studies have reported on the improvement in physical and psychological diseases through diet; however, the findings for these ameliorative effects have differed. Such differences may be due to the varying metabolism of the nutrient content in food among subjects. It has been reported that differences in the enterotypes of gut microbiota are associated with metabolic differences, and enterotypes vary between countries and regions. This study investigated whether differences in gut microbiota affect the relationship between dietary habits and stress responses.

METHODS

We administered a questionnaire to 810 subjects who participated in the "Sukoyaka Health Survey" regarding their dietary habits and stress reactions. We also performed an analysis of the gut microbiota from fecal samples.

RESULTS

The gut microbiota was grouped into four clusters based on the abundance of genus strains. The relationship between dietary habits and stress responses revealed two patterns of eating: one where more frequent intakes were associated with a lower stress response, and another with a higher stress response. We investigated the relationship between dietary habits and stress responses for each gut microbiota cluster. The results showed that the relationship between dietary habits and stress responses differed for each cluster.

CONCLUSIONS

Our analysis showed that dietary habits affect stress responses, but the relationship varies depending on the gut microbiota. This finding suggests that one of the factors for the difference in the ameliorative efficacy of physical and psychological diseases through diet is the difference in the abundance ratio of the gut microbiota (enterotype).

RNA metagenomics revealed insights into the viromes of honey bees (Apis mellifera) and Varroa mites (Varroa destructor) in Taiwan

The honey bee (Apis mellifera) is a vital pollinator for crops. However, they are infested by an ecto-parasite that has spread worldwide, Varroa mite (Varroa destructor). The Varroa mite is a vector of various western honey bee viruses. In this study, the prevalence of seven honey bee viruses (Deformed wing virus, Lake Sinai virus, Acute bee paralysis virus, Sacbrood virus, Kashmir bee virus, Black queen cell virus, Israeli acute paralysis virus), was screened with the honey bees, which were collected from fourteen apiaries from March 2023 to January 2024, and the Varroa mites, which were collected from two apiaries from July to October 2023 by using RT-PCR. Subsequently, metagenomic analyses were conducted on seven honey bee samples and two Varroa mite samples using next-generation sequencing with poly-A capture and rRNA depletion library construction methods. The results showed that 50% to 85.7% of honey bee viruses in each sample were detected by both methods, with up to three additional viruses identified when combining the two approaches. These findings underscore the importance of integrating both methods for comprehensive virome analysis. According to the virome analysis, 28 honey bee viruses were identified in honey bees and 11 in Varroa mites. Among these, 23 viruses were newly recorded in Taiwanese honey bee populations. Notably, three of the newly recorded viruses, Acute bee paralysis virus, Israeli acute paralysis virus, and Apis mellifera filamentous virus, are known to cause symptoms in honey bees, posing potential risks to their health. Six of these viruses were also detected in Varroa mites, highlighting their role in viral transmission. This study represents the first virome analysis of honey bees and Varroa mites in Taiwan, providing critical insights into honey bee health and establishing a foundation for future health assessment indices and mitigation strategies.

Integrative RNA-Seq analysis of host-parasite interactions and microbiota shifts in the gills of two fish species infected with monogeneans

Monogenean infections represent a significant threat to aquaculture by compromising fish health. These parasites can cause severe histological damage and increase mortality rates. The white snook (Centropomus viridis) and the gilthead seabream (Sparus aurata) are two commercially important fish species that become susceptible to diseases when infected with monogeneans. Understanding the molecular mechanisms underlying host responses to infection is essential for developing effective disease management strategies. In this study, we performed an integrative RNA-Seq analysis using transcriptomic datasets from C. viridis and S. aurata infected with the monogeneans Rhabdosynochus viridisi and Sparicotyle chrysophrii, respectively. These datasets originate from three studies, allowing us to investigate host gene expression changes, monogenean gene activation, and microbiota shifts associated with infection. Our analysis of the gill microbiota revealed significant alterations in bacterial composition between infected and uninfected fish. In the microbiota of both C. viridis and S. aurata, eight bacterial families were more abundant in infected fish, whereas eleven and four families, respectively, were more abundant in uninfected fish. In monogeneans, the molecular mechanisms shared across all Bioprojects included extracellular matrix organization, proteolysis, and gluconeogenesis, processes that may be involved in parasite colonization and survival within the host. In fish, our analysis identified shared molecular mechanisms between S. aurata and C. viridis, including oxygen carrier activity, cytokine regulation, bacterial response, and cadherin-mediated adhesion, highlighting a complex interplay between the host immune system, microbiota, and parasite. These findings enhance our understanding of fish-microbiome-parasite interactions and offer valuable perspectives for improving disease control strategies in aquaculture.

Linking peri-implantitis to microbiome changes in affected implants, healthy implants, and saliva: a cross-sectional pilot study

Introduction

The rising use of dental implants is accompanied by an expected increase in peri-implant diseases, particularly peri-implantitis (PI), which poses a significant threat to implant success and necessitates a thorough understanding of its pathogenesis for effective management.

Methods

To gain deeper insights into the role and impact of the peri-implant microbiome in the pathogenesis and progression of PI, we analyzed 100 samples of saliva and subgingival biofilm from 40 participants with healthy implants (HI group) or with co-occurrence of diagnosed PI-affected implants and healthy implants (PI group) using shotgun metagenomic sequencing. We identified the most discriminative species distinguishing healthy from diseased study groups through log ratios and differential ranking analyses.

Results and discussion

Mogibacterium timidum, Schaalia cardiffensis, Parvimonas micra, Filifactor alocis, Porphyromonas endodontalis, Porphyromonas gingivalis and Olsenella uli were associated with the subgingival peri-implant biofilm. In contrast, Neisseria sp oral taxon 014, Haemophilus parainfluenzae, Actinomyces naeslundii, Rothia mucilaginosa and Rothia aeria were more prevalent in the healthy peri-implant biofilm. Functional pathways such as arginine and polyamine biosynthesis, including putrescine and citrulline biosynthesis, showed stronger correlations with PI-affected implants. In contrast, peri-implant health was characterized by the predominance of pathways involved in purine and pyrimidine deoxyribonucleotide de novo biosynthesis, glucose and glucose-1-phosphate degradation, and tetrapyrrole biosynthesis. Our findings reveal that healthy implants in PI-free oral cavities differ significantly in microbial composition and functional pathways compared to healthy implants co-occurring with PI-affected implants, which more closely resemble PI-associated profiles. This pattern extended to salivary samples, where microbial and functional biomarkers follow similar trends.

Population dynamics of a bacterial consortium from a marine sediment of the Gulf of Mexico during biodegradation of the aromatic fraction of heavy crude oil

In the marine environment, uncontained crude oil is dispersed and degraded by abiotic or biotic processes; native bacterial populations gradually adapt to integrate interspecific and intraspecific metabolic networks for efficient and dynamic utilization of xenobiotic substrates as carbon source. Aromatic compounds accumulate in marine sediments and bacterial populations at these sites play a crucial role in the mobilization of those complex molecules into the global geochemical cycles. The aim of this work was to use native bacteria from a marine sediment sample in the Gulf of Mexico to enhance the biodegradation of the aromatic fraction from a heavy crude oil, as the sole carbon source, during a 200-day microcosm experiment. This process involved the gradual increase of the aromatic fraction into the culture to promote bacterial enrichment; the increase in viable cells correlated well with a biodegradation pattern of the aromatic fraction at some points. Bacterial biodiversity, as revealed by metagenomic and microbiological approaches, indicates that bacterial groups are present at all fraction concentrations, but with changes in abundance, richness and dominance. Population dynamics revealed the presence of bacteria that modify emulsification and surface tension reduction values, which could promote the incorporation of the highly hydrophobic polyaromatic compounds into the culture aqueous phase for their biodegradation by hydrocarbonoclastic bacteria present. On the other hand, the presence of non-hydrocarbonoclastic bacteria probably is sustained by cross-feeding events involving sugars, amino acids, short carbon compounds, lipids produced by the former bacteria by co-metabolism of complex aromatic substrates, which are transformed into diverse biomolecules for biofilm development to promote a bacterial population dynamics adapted to this environment.

Multi-omics analysis reveals toxicity and gut-liver axis disruption induced by polychlorinated biphenyls exposure in Yellowfin Seabream (Acanthopagrus latus)

Polychlorinated biphenyls (PCBs) are persistent organic pollutants known for their environmental persistence and bioaccumulation, posing significant health risks. This study examines the toxic effects of a representative PCBs (Aroclor 1254) on yellowfin seabream (Acanthopagrus latus) exposured for 30 days through a multi-omics approach. Histopathological examinations revealed structural damage to the intestinal structure and hepatic steatosis, along with elevated serum lipopolysaccharide levels, indicating compromised intestinal barrier integrity and liver inflammation. Metabolomic profiling showed significant alterations in lipid metabolites, including elevated lysophosphatidylcholines and arachidonic acid derivatives. Transcriptomic analysis unveiled 2272 differentially expressed genes in the liver, with notable changes in immune response and metabolic pathways. Gut microbiome analysis showed dysbiosis characterized by an increase in Proteobacteria and a decrease in Firmicutes and Actinobacteria. Remarkably, Tetranor-12S-HETE and LPC 15:1 emerged as key biomarkers for the disruption of the gut-liver axis, correlating with immune gene expression and gut microbiota composition. The integration of transcriptomic, metabolomic, and microbiome data highlighted the complex interplay between A1254 exposure and the gut-liver axis, emphasizing the central role played by PPAR signaling in mediating these effects. Collectively, these results indicate that exposure to A1254 results in bioaccumulation in the liver and gut, leading to severe tissue injury, microbiota dysbiosis, and dysregulation of the gut-liver axis, ultimately disrupting lipid metabolism. These findings underscore the metabolic health risks posed by PCBs exposure in aquatic environments.

Phylodynamic of Tomato Brown Rugose Fruit Virus and Tomato Chlorosis Virus, Two Emergent Viruses in Mixed Infections in Argentina

Tobamovirus fructirugosum (ToBRFV) and Crinivirus tomatichlorosis (ToCV) are emerging viral threats to tomato production worldwide, with expanding global distribution. Both viruses exhibit distinct biological characteristics and transmission mechanisms that influence their spread. This study aimed to reconstruct the complete genomes of ToBRFV and ToCV from infected tomato plants and wastewater samples in Argentina to explore their global evolutionary dynamics. Additionally, it compared the genetic diversity of ToBRFV in plant tissue and sewage samples. Using metagenomic analysis, the complete genome sequences of two ToBRFV isolates and two ToCV isolates from co-infected tomatoes, along with four ToBRFV isolates from sewage, were obtained. The analysis showed that ToBRFV exhibited higher genetic diversity in environmental samples than in plant samples. Phylodynamic analysis indicated that both viruses had a recent, single introduction in Argentina but predicted different times for ancestral diversification. The evolutionary analysis estimated that ToBRFV began its global diversification in June 2013 in Israel, with rapid diversification and exponential growth until 2020, after which the effective population size declined. Moreover, ToCV's global expansion was characterized by exponential growth from 1979 to 2010, with Turkey identified as the most probable location with the current data available. This study highlights how sequencing and monitoring plant viruses can enhance our understanding of their global spread and impact on agriculture.

Age-related dynamics of predominant methanogenic archaea in the human gut microbiome

BACKGROUND

The reciprocal relationship between aging and alterations in the gut microbiota is a subject of ongoing research. While the role of bacteria in the gut microbiome is well-documented, specific changes in the composition of methanogens during extreme aging and the impact of high methane production in general on health remain unclear. This study was designed to explore the association of predominant methanogenic archaea within the human gut and aging.

METHODS

Shotgun metagenomic data from the stool samples of young adults (n = 127, Age: 19-59 y), older adults (n = 86, Age: 60-99 y), and centenarians (n = 34, age: 100-109 years) were analyzed.

RESULTS

Our findings reveal a compelling link between age and the prevalence of high methanogen phenotype, while overall archaeal diversity diminishes. Surprisingly, the archaeal composition of methanogens in the microbiome of centenarians appears more akin to that of younger adults, showing an increase in Methanobrevibacter smithii, rather than Candidatus Methanobrevibacter intestini. Remarkably, Ca. M. intestini emerged as a central player in the stability of the archaea-bacteria network in adults, paving the way for M. smithii in older adults and centenarians. Notably, centenarians exhibit a highly complex and stable network of these two methanogens with other bacteria. The mutual exclusion between Lachnospiraceae and these methanogens throughout all age groups suggests that these archaeal communities may compensate for the age-related drop in Lachnospiraceae by co-occurring with Oscillospiraceae.

CONCLUSIONS

This study underscores the dynamics of archaeal microbiome in human physiology and aging. It highlights age-related shifts in methanogen composition, emphasizing the significance of both M. smithii and Ca. M. intestini and their partnership with butyrate-producing bacteria for potential enhanced health.

Oral microbiome dysbiosis in cryptogenic ischemic stroke patients with high-risk patent foramen ovale

Patent foramen ovale (PFO) is the most common congenital heart abnormality of foetal origin and has been associated with cryptogenic ischemic stroke (CIS) through several mechanisms, with most theories supporting paradoxical embolism. Other possible but unknown contributing factors, such as the role of the microbiome in PFO-associated strokes, remain unclear. We analysed saliva metagenomes to study the differences in the oral microbiome between young-onset CIS patients with clinically relevant high-risk PFO (n = 52) and those without PFO (n = 52). Age- and sex-matched stroke-free controls (n = 16) with high-risk PFO were included for the comparison. Beta diversity was significantly different between patients and controls with high-risk PFO, but not between patients with and without high-risk PFO. The phylum Ascomycota and class Saccharomycetes were significantly more abundant in patients with high-risk PFO than in those without high-risk PFO. Additionally, the abundance of Lactococcus, including Lactococcus raffinolactis and L. cremoris, was higher in controls with high-risk PFO than in patients with high-risk PFO. These findings highlight that oral dysbiosis and high-risk PFO may form a critical but under-recognized combination in the aetiology of CIS. Future research should focus on elucidating the precise mechanisms of these interactions and developing targeted interventions.

TIPP3 and TIPP3-fast: Improved abundance profiling in metagenomics

We present TIPP3 and TIPP3-fast, new tools for abundance profiling in metagenomic datasets. Like its predecessor, TIPP2, the TIPP3 pipeline uses a maximum likelihood approach to place reads into labeled taxonomies using marker genes, but it achieves superior accuracy to TIPP2 by enabling the use of much larger taxonomies through improved algorithmic techniques. We show that TIPP3 is generally more accurate than leading methods for abundance profiling in two important contexts: when reads come from genomes not already in a public database (i.e., novel genomes) and when reads contain sequencing errors. We also show that TIPP3-fast has slightly lower accuracy than TIPP3, but is also generally more accurate than other leading methods and uses a small fraction of TIPP3's runtime. Additionally, we highlight the potential benefits of restricting abundance profiling methods to those reads that map to marker genes (i.e., using a filtered marker-gene based analysis), which we show typically improves accuracy. TIPP3 is freely available at https://github.com/c5shen/TIPP3.

Inference of functional differentiation of intestinal microbes between two wild zokor species based on metagenomics

BACKGROUND

Currently, there are fewer studies on the intestinal microbes of wild zokors, and it is unclear how zokors adapt to special underground environments by regulating their intestinal microbes. Here, we explored the function of intestinal microbes of Eospalax cansus and Eospalax rothschildi based on metagenomics.

RESULTS

Both zokor species have similar intestinal microbial composition, but E. cansus has a higher proportion of bacteria involved in carbohydrate degradation. Functional analysis based on KEGG and CAZy databases indicated that the intestinal microbes of E. cansus harboured stronger carbohydrate degradation ability, mainly in starch and sucrose metabolism, and further in cellulose degradation. Furthermore, the cellulase activity was significantly higher in E. cansus than that in E. rothschildi. Eospalax cansus has a stronger microbial fermentation ability due to an increase in fibre-degrading bacteria like unclassified_f_Lachnospiraceae, Ruminococcus, and Clostridium. In addition, the dominant bacteria isolated from zokor were Bacillus, some of which could degrade both cellulose and hemicellulose.

CONCLUSION

Metagenomic analysis and bacterial isolation experiments indicate that E. cansus has a stronger microbial cellulose-degrading capacity, possibly as an adaptation to its limited food resources underground. © 2024 Society of Chemical Industry.

Viral and host factors associated with SARS-CoV-2 disease severity in Georgia, USA

While SARS-CoV-2 vaccines have shown strong efficacy, the continued emergence of new viral variants raises concerns about the ongoing and future public health impact of COVID-19, especially in locations with suboptimal vaccination uptake. We investigated viral and host factors, including vaccination status, that were associated with SARS-CoV-2 disease severity in a setting with low vaccination rates. We analyzed clinical and demographic data from 1,957 individuals in the state of Georgia, USA, coupled with viral genome sequencing from 1,185 samples. We found no specific mutations associated with disease severity. Compared to those who were unvaccinated, vaccinated individuals experienced less severe SARS-CoV-2 disease, and the effect was similar for both variants. Vaccination within the prior 3-9 months was associated with decreased odds of moderate disease, severe disease, and death. Older age and underlying health conditions, especially immunosuppression and renal disease, were associated with increased disease severity. Overall, this study provides insights into the impact of vaccination status, variants/mutations, and clinical factors on disease severity in SARS-CoV-2 infection when vaccination rates are low. Understanding these associations will help refine and reinforce messaging around the crucial importance of vaccination in mitigating the severity of SARS-CoV-2 disease.

Reevaluation of the gastrointestinal methanogenic archaeome in multiple sclerosis and its association with treatment

The role of the gut archaeal microbiome (archaeome) in health and disease remains poorly understood. Methanogenic archaea have been linked to multiple sclerosis (MS), but prior studies were limited by small cohorts and inconsistent methodologies. To address this, we re-evaluated the association between methanogenic archaea and MS using metagenomic data from the International Multiple Sclerosis Microbiome Study. We analyzed gut microbiome profiles from 115 MS patients and 115 healthy household controls across Buenos Aires (27.8%), Edinburgh (33.9%), New York (10.4%), and San Francisco (27.8%). Metagenomic sequences were taxonomically classified using kraken2/bracken and a curated profiling database to detect archaea, specifically Methanobrevibacter species. Most MS patients were female (80/115), aged 25-72 years (median: 44.5), and 70% were undergoing treatment, including dimethyl fumarate (n = 21), fingolimod (n = 20), glatiramer acetate (n = 14), interferon (n = 18), natalizumab (n = 6), or ocrelizumab/rituximab (n = 1). We found no significant differences in overall archaeome profiles between MS patients and controls. However, treated MS patients exhibited higher abundances of Methanobrevibacter smithii and M. sp900766745 compared to untreated patients. Notably, M. sp900766745 abundance correlated with lower disease severity scores in treated patients. Our results suggest that gut methanogens are not directly associated with MS onset or progression but may reflect microbiome health during treatment. These findings highlight potential roles for M. smithii and M. sp900766745 in modulating treatment outcomes, warranting further investigation into their relevance to gut microbiome function and MS management.IMPORTANCEMultiple sclerosis (MS) is a chronic neuroinflammatory disease affecting the central nervous system, with approximately 2.8 million people diagnosed worldwide, mainly young adults aged 20-30 years. While recent studies have focused on bacterial changes in the MS microbiome, the role of gut archaea has been less explored. Previous research suggested a potential link between methanogenic archaea and MS disease status, but these findings remained inconclusive. Our study addresses this gap by investigating the gut archaeal composition in MS patients and examining how it changes in response to treatment. By focusing on methanogens, we aim to uncover novel insights into their role in MS, potentially revealing new biomarkers or therapeutic targets. This research is crucial for enhancing our understanding of the gut microbiome's impact on MS and improving patient management.

Fecal Microbial Profiles and Short-Chain Fatty Acid/Bile Acid Metabolomics in Patients With Age-Related Macular Degeneration: A Pilot Study

Purpose

Age-related macular degeneration (AMD) is a multifactorial disease, and studies have implicated the role of gut microbiota in its pathogenesis. However, characterization of microbiome dysbiosis and associated microbial-derived metabolomic profiles across AMD stages remains unknown. In this pilot study, we explored how gut microbiome composition and gut-derived metabolites differ in AMD.

Methods

Our pilot study analyzed fasted stool samples that were collected from 22 patients at a tertiary academic center. Subjects were classified as control, intermediate AMD, or advanced AMD based on clinical presentation. 16S rRNA amplicon sequencing and standard chromatography-mass spectrometry methods were used to identify bacterial taxonomy composition and abundance of short-chain fatty acids (SCFAs) and bile acids (BAs), respectively. Genetic testing was used to investigate the frequency of 14 high-risk single nucleotide polymorphisms (SNPs) associated with AMD in the AMD cohort.

Results

Forty-three differentially abundant genera were present among the control, intermediate, and advanced groups. Taxa with known roles in immunologic pathways, such as Desulfovibrionales (q = 0.10) and Terrisporobacter (q = 1.16e-03), were in greater abundance in advanced AMD patients compared to intermediate. Advanced AMD patients had decreased abundance of 12 SCFAs, including acetate (P = 0.002), butyrate (P = 0.04), and propionate (P = 0.01), along with 12 BAs, including taurocholic acid (P = 0.02) and tauroursodeoxycholic acid (P = 0.04). Frequencies of high-risk SNPs were not significantly different between the intermediate and advanced AMD groups.

Conclusions

This pilot study identifies distinct gut microbiome compositions and metabolomic profiles associated with AMD and its stages, providing preliminary evidence of a potential link between gut microbiota and AMD pathogenesis. To validate these findings and elucidate the underlying mechanisms, future research with larger cohorts and more comprehensive sampling is strongly recommended.

Characterization of vaginal microbiomes in clinician-collected bacterial vaginosis diagnosed samples

Bacterial vaginosis (BV) is a type of vaginal inflammation caused by bacterial overgrowth, upsetting the healthy microbiome of the vagina. Existing clinical testing for BV is primarily based upon physical and microscopic examination of vaginal secretions. Modern PCR-based clinical tests target panels of BV-associated microbes, such as the Labcorp NuSwab test that targets Atopobium (Fannyhessea) vaginae, Megasphaera-1, and Bacterial Vaginosis Associated Bacterium (BVAB)-2. Remnant clinician-collected NuSwab vaginal swabs underwent DNA extraction and 16S V3-V4 rRNA gene sequencing to profile microbes in addition to those included in the Labcorp NuSwab test. Community state types (CSTs) were determined using the most abundant taxon detected in each sample. PCR results for NuSwab panel microbial targets were compared against the corresponding microbiome profiles. Metabolic pathway abundances were characterized via metagenomic prediction from amplicon sequence variants (ASVs). 16S V3-V4 rRNA gene sequencing of 75 remnant vaginal swabs yielded 492 unique 16S V3-V4 ASVs, identifying 83 unique genera. NuSwab microbe quantification was strongly concordant with quantification by sequencing (P < 0.01). Samples in CST-I (18 of 18, 100%), CST-II (three of three, 100%), CST-III (15 of 17, 88%), and CST-V (one of one, 100%) were largely categorized as BV-negative via the NuSwab panel, while most CST-IV samples (28 of 36, 78%) were BV-positive or BV-indeterminate. BV-associated microbial and predicted metabolic signatures were shared across multiple CSTs. These findings highlight robust sequencing-based quantification of Labcorp NuSwab BV microbes, accurate discrimination of vaginal microbiome CSTs dominated by distinct Lactobacilli, and expanded the identification of BV-associated bacterial and metabolic biomarkers.IMPORTANCEBacterial vaginosis (BV) poses a significant health burden for women during reproductive years and onward. Current BV diagnostics rely on either panels of select microbes or on physical and microscopic evaluations by technicians. Here, we sequenced the microbiome profiles of samples previously diagnosed by the Labcorp NuSwab test to better understand disruptions to the vaginal microbiome during BV. We show that microbial sequencing can faithfully reproduce targeted PCR diagnostic results and can improve our knowledge of healthy and BV-associated microbial and metabolic biomarkers. This work highlights a robust, agnostic BV classification scheme with potential for future development of sequencing-based BV diagnostic tools.

Polyvinyl chloride microplastic triggers bidirectional transmission of antibiotic resistance genes in soil-earthworm systems

The diffusion and distribution of ubiquitous microplastics and antibiotic resistance genes (ARGs) in soil ecosystems are easily influenced by earthworm activity. However, minimal research exists on the bidirectional dissemination of ARGs in the soil-earthworm ecosystems under microplastic stress. Focusing on the typical microplastic polyvinyl chloride (PVC) microspheres in simulated soil-earthworm (Eisenia fetida) systems, we characterized the PVC-triggered interactive transmission of ARGs between earthworm guts and their dwelling soils using shotgun metagenomics and qPCR methodologies. PVC exposure did not alter the diversity and relative abundance of ARGs in earthworm-uninoculated soils but significantly increased those in earthworm-inoculated soils. Meanwhile, the abundance of ARGs increased in the earthworm gut under PVC stress. Source tracking analysis showed a higher source proportion of soil-borne ARGs into earthworm gut under PVC treatments. Mechanistically, PVC-triggered increasing prevalence of ARGs was significantly related to both the bacterial community and mobile genetic elements-mediated horizontal transfer in the soils, whereas the bacterial community predominated the process in the earthworm guts. Overall, our findings reveal a PVC-triggered bidirectional transmission pattern of ARGs between earthworm guts and their dwelling soils and highlight the overlooked ecotoxicological risk of microplastics in soil-earthworm systems.

Characterization of enteric pathogens in Harare, Zimbabwe using environmental surveillance and metagenomics

High diarrheal disease burden remains an urgent concern in low- and middle-income countries, greatly affecting children under the age of 5 years and those living with HIV and AIDS. Treatment of infectious diseases has also become increasingly difficult with the rapid rise of antimicrobial resistance (AMR). Environmental surveillance of wastewater can supplement gaps in clinical surveillance as residents on a sewage system contribute to the wastewater, providing simple, composite samples that can improve understanding about both pathogens and AMR in the community. This study evaluated the effectiveness of environmental surveillance with shotgun metagenomics as a tool to characterize a broad range of enteric pathogens, antibiotic resistance genes, and virulence factor genes (VFGs) in wastewater from six neighborhoods in Harare, Zimbabwe. Alpha and beta diversity of the microbial community were similar between high-income and low-income suburbs. Enteric pathogens of high AMR and clinical concern, including Staphylococcus aureus, Pseudomonas aeruginosa, and Salmonella enterica, were detected in all samples. The top VFGs were encoded for delivery, adherence, and motility, functions important in toxin secretion, colonization, and immune modulation. The findings provide a foundation for future studies to explore environmental surveillance and shotgun metagenomics as a public health monitoring tool for enteric diseases.

Pond water microbiome antibiotic resistance genes vary seasonally with environmental pH and tannins

Microbial communities of small freshwater bodies interact dynamically with environmental factors in unknown ways. Longitudinal sampling of four ponds in Knox County, Ohio, revealed relationships among antibiotic resistance genes (ARGs) and environmental factors such as pH and tannin concentrations. For each site, microbial communities were collected by filtration, and metagenomes were analyzed by short-read sequencing. ARGs were quantified using the ShortBRED pipeline to detect and quantify hits to a marker set derived from the Comprehensive Antibiotic Resistance Database. The top 30 ARGs showed increased abundance at the end of the growing season. The top two ARGs with the largest marker hits encode components of a Stenotrophomonas drug efflux pump powered by proton-motive force (smeABC) and a mycobacterial global regulator that activates a drug pump and acid stress response (mtrA). The smeABC and mtrA prevalence showed a modest correlation with acidifying conditions (low pH and high tannic acids). Acidity amplifies the transmembrane pH difference component of the proton-motive force, thus increasing the cell's energy available for pump function and ARG expression. Association with microbial taxa was tested by the Kraken2/Bracken predictor of taxa profiles. The ARG profiles showed the strongest acid dependence in ponds with a high proportion of Proteobacteria, whereas a pond with high Cyanobacteria showed the lowest ARG counts. Efflux pumps such as SmeABC and transcriptional activation by MtrA incur large energy expenditures whose function may be favored at low external pH, where the cell's proton-motive force is maximal.

IMPORTANCE

Compared to rivers and lakes, pond microbial ecosystems are understudied despite close contact with agriculture and recreation. Environmental microbes offer health benefits as well as hazards for human contact. Small water bodies may act as reservoirs for drug-resistant organisms and transfer of antibiotic resistance genes (ARGs). Yet, the public is rarely aware of the potential for exposure to ARG-carrying organisms in recreational water bodies. Little is known about the capacity of freshwater microbial communities to remediate drug pollution and which biochemical factors may select against antibiotic resistance genes. This study analyzes how aquatic ARG prevalence may depend on environmental factors such as pH and tannic acid levels.

Temporal dynamics and metagenomics of phosphorothioate epigenomes in the human gut microbiome

BACKGROUND

Epigenetic regulation of gene expression and host defense is well established in microbial communities, with dozens of DNA modifications comprising the epigenomes of prokaryotes and bacteriophage. Phosphorothioation (PT) of DNA, in which a chemically reactive sulfur atom replaces a non-bridging oxygen in the sugar-phosphate backbone, is catalyzed by dnd and ssp gene families widespread in bacteria and archaea. However, little is known about the role of PTs or other microbial epigenetic modifications in the human microbiome. Here we optimized and applied fecal DNA extraction, mass spectrometric, and metagenomics technologies to characterize the landscape and temporal dynamics of gut microbes possessing PT modifications.

RESULTS

Exploiting the nuclease-resistance of PTs, mass spectrometric analysis of limit digests of PT-containing DNA reveals PT dinucleotides as part of genomic consensus sequences, with 16 possible dinucleotide combinations. Analysis of mouse fecal DNA revealed a highly uniform spectrum of 11 PT dinucleotides in all littermates, with PTs estimated to occur in 5-10% of gut microbes. Though at similar levels, PT dinucleotides in fecal DNA from 11 healthy humans possessed signature combinations and levels of individual PTs. Comparison with a widely distributed microbial epigenetic mark, m6dA, suggested temporal dynamics consistent with expectations for gut microbial communities based on Taylor's Power Law. Application of PT-seq for site-specific metagenomic analysis of PT-containing bacteria in one fecal donor revealed the larger consensus sequences for the PT dinucleotides in Bacteroidota, Bacillota (formerly Firmicutes), Actinomycetota (formerly Actinobacteria), and Pseudomonadota (formerly Proteobacteria), which differed from unbiased metagenomics and suggested that the abundance of PT-containing bacteria did not simply mirror the spectrum of gut bacteria. PT-seq further revealed low abundance PT sites not detected as dinucleotides by mass spectrometry, attesting to the complementarity of the technologies. Video Abstract CONCLUSIONS: The results of our studies provide a benchmark for understanding the behavior of an abundant and chemically reactive epigenetic mark in the human gut microbiome, with implications for inflammatory conditions of the gut.

A Two-Phage Cocktail Modulates Gut Microbiota Composition and Metabolic Profiles in an Ex Vivo Colon Model

Bacteriophage therapy is a promising approach for targeting antibiotic-resistant bacteria and modulating gut microbiota in metabolic diseases such as obesity. This study evaluated the impact of a two-phage cocktail on an ex vivo colonic simulation model of gut microbiota derived from obese individuals, both in its normalized state and after enrichment with Enterobacter cloacae, an obesity-related bacteria. Microbiological analyses confirmed that the phage cocktail remained active throughout the colonic regions over three digestion cycles and effectively reduced enterobacterial populations in the enriched microbiota. Metabarcoding of the 16S rRNA gene revealed that phage therapy did not significantly alter the abundance of dominant genera, but selectively reduced E. cloacae across all colonic regions. Alpha diversity was significantly affected only in the enriched microbiota, while beta diversity analysis indicated significant compositional shifts during therapy, with reduced dispersion in the final treatment stage. Short-chain fatty acid profiling demonstrated region- and group-specific metabolic responses, with increased lactic and butyric acid concentrations in the ascending colon of the enriched microbiota following phage treatment. This study provides the first ex vivo evidence that a two-phage cocktail can selectively eliminate E. cloacae while preserving overall microbiota structure and functionality. These findings establish a foundation for future in vivo studies exploring the role of phage therapy in reshaping gut microbial communities and metabolic profiles, highlighting its potential as a precision tool for managing gut dysbiosis in metabolic disorders.

Antimicrobial resistance of Vibrio spp. from the coastal California system: discordance between genotypic and phenotypic patterns

Antimicrobial resistance in Vibrio species poses risks to both human and marine mammal health. Whole genome sequencing of Vibrio spp. can be utilized to screen for antimicrobial resistance genes and allelic variants to provide mechanistic insights in ways that PCR screening and phenotypic interpretation cannot. Our goals were to (i) characterize antimicrobial resistance patterns of Vibrio spp. pathogens isolated from southern sea otters (Enhydra lutris nereis), northern sea otters (Enhydra lutris kenyoni), and environmental samples from the central California coast using whole genome sequencing, and (ii) compare the presence of antimicrobial resistance genes with phenotypic interpretation from antibiotic susceptibility testing. Unexpectedly, genomic classification identified an understudied species, Vibrio diabolicus, in sea otter and environmental isolates that were previously identified as Vibrio alginolyticus. A total of 489 Vibrio spp. isolates were sequenced, and frequently detected antimicrobial resistance genes included multidrug efflux pumps and genes associated with resistance to ß-lactams and tetracyclines. Genes associated with resistance to fluoroquinolones, aminoglycosides, chloramphenicol, and sulfonamides were uncommon. Sea otter isolates were phenotypically susceptible to tetracycline despite carrying genes tet34 and tet35. Both between- and within-species variations in ampicillin resistance were observed despite the ubiquitous presence of blaCARB genes in V. alginolyticus, V. diabolicus, and Vibrio parahaemolyticus. Discordance between phenotypic and genotypic ampicillin resistance was especially noted for V. parahaemolyticus and was partially attributed to the allelic variation of the blaCARB genes. Tetracyclines and fluoroquinolones, but not ß-lactams, are likely to be effective treatments for vibriosis in sea otters.

IMPORTANCE

Vibriosis (infection with non-cholera Vibrio spp.) is the most common seafood-borne illness globally, with major impacts on public health, food security, and wildlife health. Potential treatments of antimicrobial-resistant Vibrio spp. in humans, aquaculture, and marine wildlife rehabilitation are complicated by current diagnostic challenges regarding bacterial species identification and interpretation of antimicrobial resistance patterns. Unexpected detection of previously misidentified Vibrio diabolicus in sea otters suggests that a broader taxonomic group of Vibrio infect sea otters than previously described. We also determined that the presence of ß-lactamase genes alone in sea otter isolates does not necessarily correlate with an ampicillin-resistant phenotype, likely due to deleterious amino acid substitutions in certain blaCARB alleles. Continued monitoring of Vibrio spp. phenotypes and genotypes in sea otters is warranted to observe biologically relevant changes in antimicrobial resistance.

Retrospective analysis of antimicrobial resistance associated with bovine respiratory disease

The administration and utility of antibiotics to control and treat bovine respiratory disease (BRD) in beef cattle feedlots is a growing concern. Antimicrobial resistance (AMR) among BRD-associated bacterial pathogens has been the subject of cultivation-dependent and cultivation-independent surveillance. Bacterial genome sequencing and metagenomic approaches facilitate the characterization of AMR in the beef industry; however, the current collection of cattle-associated AMR research programs lack connections to each other. A more integrated view of how antimicrobial use (AMU) is related to resistance at a gene level is needed. We sought to establish a catalog of commonly observed AMR genes (ARGs) in opportunistic bacterial pathogens that contribute to BRD using publicly available data sets that were generated by the scientific community with and without AMU in mind. The presence of these clinically relevant ARGs appeared to differ by geography. Greater sampling in North America facilitated the generation of a list of ARGs often encoded by Mannheimia haemolytica and Pasteurella multocida. Detection of clinically relevant ARGs in shotgun metagenomes of cattle-associated and accessible feedlot samples such as water, soil, and feces was possible but limited by relative sequence read abundance. An exception was the tylosin esterase-encoding gene estT, which is among the most frequently observed ARGs in M. haemolytica and feedlot-related metagenomic data sets. Finally, by re-evaluating studies on the impact of AMU on AMR in beef production systems, we show that conventional practices, including in-feed antibiotic use, increase the relative abundance of ARGs in animal-derived samples.IMPORTANCEThis retrospective analysis delivers a list of ARGs found in opportunistic pathogens that contribute to BRD. The high incidence of BRD in North America is linked to the origin and implementation of metaphylaxis to mitigate detrimental animal losses at feedlots. Notably, ARGs commonly observed in these pathogens isolated in North America were not conserved across the globe, underscoring the relationship between regional AMU and AMR. A positive relationship was also observed between the relative abundance of ARGs in cattle-associated metagenomes with greater exposure to antibiotics. Overall, this analysis should help to guide future surveillance efforts and experimental designs to more directly evaluate the impacts of feedlot practices on AMR.

Jellyfish blooms-an overlooked hotspot and potential vector for the transmission of antimicrobial resistance in marine environments

Gelatinous zooplankton (GZ) represents an important component of marine food webs, capable of generating massive blooms with severe environmental impact. When these blooms collapse, considerable amounts of organic matter (GZ-OM) either sink to the seafloor or can be introduced into the ocean's interior, promoting bacterial growth and providing a colonizable surface for microbial interactions. We hypothesized that GZ-OM is an overlooked marine hotspot for transmitting antimicrobial resistance genes (ARGs). To test this, we first re-analyzed metagenomes from two previous studies that experimentally evolved marine microbial communities in the presence and absence of OM from Aurelia aurita and Mnemiopsis leidyi recovered from bloom events and thereafter performed additional time-resolved GZ-OM degradation experiments to improve sample size and statistical power of our analysis. We analyzed these communities for composition, ARG, and mobile genetic element (MGE) content. Communities exposed to GZ-OM displayed up to fourfold increased relative ARG and up to 10-fold increased MGE abundance per 16S rRNA gene copy compared to the controls. This pattern was consistent across ARG and MGE classes and independent of the GZ species, indicating that nutrient influx and colonizable surfaces drive these changes. Potential ARG carriers included genera containing potential pathogens raising concerns of ARG transfer to pathogenic strains. Vibrio was pinpointed as a key player associated with elevated ARGs and MGEs. Whole-genome sequencing of a Vibrio isolate revealed the genetic capability for ARG mobilization and transfer. This study establishes the first link between two emerging issues of marine coastal zones, jellyfish blooms and ARG spread, both likely increasing with future ocean change. Hence, jellyfish blooms are a quintessential "One Health" issue where decreasing environmental health directly impacts human health.IMPORTANCEJellyfish blooms are, in the context of human health, often seen as mainly problematic for oceanic bathing. Here we demonstrate that they may also play a critical role as marine environmental hotspots for the transmission of antimicrobial resistance (AMR). This study employed (re-)analyses of microcosm experiments to investigate how particulate organic matter introduced to the ocean from collapsed jellyfish blooms, specifically Aurelia aurita and Mnemiopsis leidyi, can significantly increase the presence of antimicrobial resistance genes and mobile genetic elements in marine microbial communities by up to one order of magnitude. By providing abundant nutrients and surfaces for bacterial colonization, organic matter from these blooms enhances ARG proliferation, including transfer to and mobility in potentially pathogenic bacteria like Vibrio. Understanding this connection highlights the importance of monitoring jellyfish blooms as part of marine health assessments and developing strategies to mitigate the spread of AMR in coastal ecosystems.

Identification of causative agents of infective endocarditis by metagenomic next-generation sequencing of resected valves

Background

Infective endocarditis (IE) is a rare and life-threatening condition with considerable mortality rates. Diagnosis is often complicated by negative blood culture results, limiting the accurate identification of causative pathogens. This study aimed to evaluate the effectiveness of metagenomic next-generation sequencing (mNGS) of cardiac valve specimens compared to conventional clinical laboratory methods for identifying pathogens in IE.

Methods

Nineteen patients with suspected IE who were scheduled for surgical valve removal were prospectively enrolled. The metagenomic workflow included bacterial DNA enrichment from resected valves using the Molzym Ultra-Deep Microbiome Prep, sequencing of metagenomic libraries using the Illumina MiSeq platform, and Kraken 2 taxonomic assignments based on read data.

Results

Valve mNGS achieved a sensitivity of 82.4% and a specificity of 100% relative to the final adjudicated pathogen diagnosis. Blood culture, considered the reference standard, exhibited slightly higher sensitivity (88.2%) with comparable specificity (100%). In comparison, valve culture (sensitivity: 29.4%, specificity: 50.0%) and microscopy (sensitivity: 35.3%, specificity: 100%) showed lower diagnostic performance. Delays between blood culture negativization and valve resection impacted mNGS sensitivity, likely due to pathogen clearance. Notably, valves resected within 12 days from blood culture negativization achieved 100% diagnostic accuracy, emphasizing the importance of timing for optimal mNGS results.

Conclusion

This study underscores mNGS as a valuable diagnostic tool for detecting IE pathogens, complementing traditional diagnostic methods. The detection of antibiotic resistance genes and multi-locus sequence typing profiles in some samples further demonstrated its utility.

Anaerobic digestion at hyper-mesophilic temperatures: Microbiome and antibiotic resistome in full-scale agricultural biogas plants

Temperatures between 40°C and 50°C are increasingly implemented in full-scale agricultural anaerobic digestion (AD), yet the microbial diversity and antibiotic resistome dynamics within this temperature range remain poorly understood. Here, we defined this range as "hyper-mesophilic" and surveyed five full-scale sites. Significant differences were found in the bacterial community structure, potentially stemming from feedstock combination (high vs low/non-manure) and operating temperature. Sites operating at 44°C exhibited superior attenuation efficiency (81-92 %) for antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) than sites operating at 41°C (41-83 %). High-risk clinically important ARGs such as sul1, lnuA, tet(O), and tet(L) persisted in sites blending livestock manure. Potential hosts of ARGs were identified and included opportunistic human pathogens like Enterococcus faecalis, Staphylococcus aureus, and Clostridioides difficile. The tnpA transposon accounted for > 50 % of the total MGEs and frequently co-localised with ARGs, while the class 1 integrase, intI1, was only detected in manure-blended AD. Based on prevalence in plasmids, ARGs showed higher mobility potential in sites blending chicken manure. The results obtained here provided initial insights into hyper-mesophilic AD and reinforced the importance of conducting surveillance for crop AD, with or without manure, as part of wider efforts to mitigate antimicrobial resistance in agroecosystems.

Metagenomic insights of microbial functions under conventional and conservation agriculture

Agricultural practices such as conventional (CN) and conservation agriculture (CA) influence the composition and structure of soil microorganisms. We used short reads and genome-resolved metagenomic-based dual sequencing approaches to create a profile of bacterial and archaeal communities in hyperthermic Typic Haplustepts soil after seven years of CA and CN. The most differences in the physico-chemical and biological properties of soil were higher pH, organics carbon, available nitrogen and microbial biomass contents, activities of dehydrogenase, β-glucosidase, and arylsulfatase, found in CA soil. The dominant bacterial taxa under both management types were Pseudomonadota (46-48%), Acidobacteriota (12-13%), Planctomycetota (8-10%), Bacteroidota (7-8%), and Actinomycetota (6-7%). Nitrososphaerota (1.1-1.5%) was the predominant archaeal phyla in CA and CN soils. The alpha diversity was 1.5 times higher in CA compared to CN soils. Fourteen high-quality (HQ) metagenomic-assembled genomes (MAGs) were recovered from both groups. Four HQ metagenome-assembled genomes (MAGs) from the Pseudomonadota phylum were exclusively recovered from the CA soil. The dominance of this phylum in the CA soil might be correlated with its nutrient richness, as certain classes of Pseudomonadota, such as Alpha, Beta-, Gamma-, and Deltaproteobacteria, are known to be copiotrophic. Copiotrophic organisms thrive in nutrient-rich environments, which could explain their prevalence in the CA soil. CAZyme gene analysis showed that Glycoside Hydrolases (GH) and GlycosylTransferases (GT) classes are dominant in the CA group, possibly due to higher substrate availability from the application of crop residues, which provide a rich source of complex carbohydrates. Several biogeochemical gene families related to C1 compounds, hydrogen, oxygen, and sulfur metabolism were enriched in CA soils, suggesting these practices may contribute to a soil environment with increased organic matter content, microbial diversity, and nutrient availability. Overall, CA practices seemed to improve soil health by supporting soil microbial communities abundance.

Bioinformatic approaches to blood and tissue microbiome analyses: challenges and perspectives

Advances in next-generation sequencing have resulted in a growing understanding of the microbiome and its role in human health. Unlike traditional microbiome analysis, blood and tissue microbiome analyses focus on the detection and characterization of microbial DNA in blood and tissue, previously considered a sterile environment. In this review, we discuss the challenges and methodologies associated with analyzing these samples, particularly emphasizing blood and tissue microbiome research. Key preprocessing steps-including the removal of ribosomal RNA, host DNA, and other contaminants-are critical to reducing noise and accurately capturing microbial evidence. We also explore how taxonomic profiling tools, machine learning, and advanced normalization techniques address contamination and low microbial biomass, thereby improving reliability. While it offers the potential for identifying microbial involvement in systemic diseases previously undetectable by traditional methods, this methodology also carries risks and lacks universal acceptance due to concerns over reliability and interpretation errors. This paper critically reviews these factors, highlighting both the promise and pitfalls of using blood and tissue microbiome analyses as a tool for biomarker discovery.

Evaluating stool microbiome integrity after domestic freezer storage using whole-metagenome sequencing, genome assembly, and antimicrobial resistance gene analysis

The gut microbiome is crucial for host health. Early childhood is a critical period for the development of a healthy gut microbiome, but it is particularly sensitive to external influences. Recent research has focused on using advanced techniques like shotgun metagenome sequencing to identify key microbial signatures and disruptions linked to disease. For accurate microbiome analysis, samples need to be collected and stored under specific conditions to preserve microbial integrity and composition, with -80°C storage considered the gold standard for stabilization. This study investigates the effect of domestic freezer storage on the microbial composition of stool samples obtained from 20 children under 4 years of age with the use of shotgun metagenome sequencing. Fresh stool samples were aliquoted into sterile tubes, with one aliquot stored at 4°C and analyzed within 24 hours, while others were frozen in domestic freezers (below -18°C) and analyzed after 1 week, 2 months, and 6 months. Assessments of contig assembly quality, microbial diversity, and antimicrobial resistance genes revealed no significant degradation or variation in microbial composition.

IMPORTANCE

Most prior studies on sample storage have relied on amplicon sequencing, which is less applicable to metagenome sequencing-given considerations of contig quality and functional gene detection-and less reliable in representing microbial composition. Moreover, the effects of domestic freezer storage for at-home stool collection on microbiome profiles, contig quality, and antimicrobial resistance gene profiles have not been previously investigated. Our findings suggest that stool samples stored in domestic freezers for up to 6 months maintain the integrity of metagenomic data. These findings indicate that domestic freezer storage does not compromise the integrity or reproducibility of metagenomic data, offering a reliable and accessible alternative for temporary sample storage. This approach enhances the feasibility of large-scale at-home stool collection and citizen science projects, even those focused on the more easily perturbed early life microbiome. This advancement enables more inclusive research into the gut microbiome, enhancing our understanding of its role in human health.

Metatranscriptomics reveals gene expression dynamics during an anatoxin-a producing Dolichospermum bloom in a western coastal lake

Cyanobacteria harmful algal blooms in lakes are primarily driven by nutrient and temperature conditions, yet the interplay of these abiotic factors with microbial community dynamics during bloom events is complex and challenging to unravel. Despite advances through deep sequencing approaches, the underlying transcriptomic changes occurring within blooming and non-blooming taxa remains an actively expanding area of study. In this work, we examined a spring-summer bloom event in Anderson Lake, WA, which has experienced recurring annual blooms dominated by the filamentous, anatoxin-a producing, diazotroph: Dolichospermum sp. WA102. Our data reveal the overall transcriptional dominance by Dolichospermum sp. WA102 during the bloom, initiated with increasing temperature and light intensity under high available phosphorus but low nitrogen conditions. We find that heterocyst differentiation was already transcriptionally initiated prior to the bloom, facilitating downstream gene cascades necessary for rapid nitrogen fixation and metabolism. As the bloom progresses, phosphorus becomes depleted, necessitating the expression of Pho regulon components in Dolichospermum sp. WA102 and possibly curtailing the bloom itself. We dissect toxin production and the transcriptional subtleties of the anatoxin-a synthesis locus. Additionally, co-occurring taxa exhibited distinct gene expression profiles, with competition for nutrients, light, and potential allelopathic interactions acting as drivers. Overall, our data provide a unique transcriptomic perspective on a single-taxa-driven, anatoxin-producing bloom, highlighting its competitive adaptation to nutrient acquisition and favorable conditions. This deeper understanding of the genetic mechanisms underlying algal bloom events may aid in predicting and preventing future blooms.

The effect of commonly employed forensic DNA extraction protocols on ssDNA/dsDNA proportion and DNA integrity

The utilisation of massively parallel sequencing (MPS) in forensic DNA analysis is on the rise, driven by the expansion of targeted MPS panels in the market and the introduction of forensic investigative genetic genealogy. The MPS library preparation process, integral to both whole-genome sequencing (WGS) and targeted MPS panel data generation, is largely based on converting double-stranded DNA (dsDNA) into sequencing libraries. In the current study, we examined the effect of seven routinely used forensic DNA extraction methods on the strandedness (single-stranded or double-stranded) and the fragment size of the DNA extracted from buccal swab, blood, bone and tooth samples. Our findings reveal a variation in the proportion of dsDNA and single-stranded DNA (ssDNA), with the phenol-chloroform and silica column-based extraction methods tested predominantly yielding dsDNA, while the tested Chelex and magnetic bead-based extraction methods predominantly yielded ssDNA. Additionally, fragment size analysis showed that high molecular weight dsDNA was recovered from buccal swab samples with all of the extraction methods except Chelex, which yielded relatively short dsDNA fragments. DNA extracted from tooth samples with tested magnetic bead-based extraction methods resulted in longer dsDNA fragments compared to the silica column-based extraction protocol.

Metagenomic estimation of dietary intake from human stool

Dietary intake is tightly coupled to gut microbiota composition, human metabolism and the incidence of virtually all major chronic diseases. Dietary and nutrient intake are usually assessed using self-reporting methods, including dietary questionnaires and food records, which suffer from reporting biases and require strong compliance from study participants. Here, we present Metagenomic Estimation of Dietary Intake (MEDI): a method for quantifying food-derived DNA in human faecal metagenomes. We show that DNA-containing food components can be reliably detected in stool-derived metagenomic data, even when present at low abundances (more than ten reads). We show how MEDI dietary intake profiles can be converted into detailed metabolic representations of nutrient intake. MEDI identifies the onset of solid food consumption in infants, shows significant agreement with food frequency questionnaire responses in an adult population and shows agreement with food and nutrient intake in two controlled-feeding studies. Finally, we identify specific dietary features associated with metabolic syndrome in a large clinical cohort without dietary records, providing a proof-of-concept for detailed tracking of individual-specific, health-relevant dietary patterns without the need for questionnaires.