Short-term exposure to antibiotics begets long-term disturbance in gut microbial metabolism and molecular ecological networks.

BACKGROUND: Antibiotic exposure can occur in medical settings and from environmental sources. Long-term effects of brief antibiotic exposure in early life are largely unknown. RESULTS: Post a short-term treatment by ceftriaxone to C57BL/6 mice in early life, a 14-month observation was performed using 16S rRNA gene-sequencing technique, metabolomics analysis, and metagenomics analysis on the effects of ceftriaxone exposure. Firstly, the results showed that antibiotic pre-treatment significantly disturbed gut microbial α and ß diversities (P < 0.05). Both Chao1 indices and Shannon indices manifested recovery trends over time, but they didn't entirely recover to the baseline of control throughout the experiment. Secondly, antibiotic pre-treatment reduced the complexity of gut molecular ecological networks (MENs). Various network parameters were affected and manifested recovery trends over time with different degrees, such as nodes (P < 0.001, R2 = 0.6563), links (P < 0.01, R2 = 0.4543), number of modules (P = 0.0672, R2 = 0.2523), relative modularity (P = 0.6714, R2 = 0.0155), number of keystones (P = 0.1003, R2 = 0.2090), robustness_random (P = 0.79, R2 = 0.0063), and vulnerability (P = 0.0528, R2 = 0.28). The network parameters didn't entirely recover. Antibiotic exposure obviously reduced the number of key species in gut MENs. Interestingly, new keystones appeared during the recovery process of network complexity. Changes in network stability might be caused by variations in network complexity, which supports the ecological theory that complexity begets stability. Besides, the metabolism profiles of the antibiotic group and control were significantly different. Correlation analysis showed that antibiotic-induced differences in gut microbial metabolism were related to MEN changes. Antibiotic exposure also caused long-term effects on gut microbial functional networks in mice. CONCLUSIONS: These results suggest that short-term antibiotic exposure in early life will cause long-term negative impacts on gut microbial diversity, MENs, and microbial metabolism. Therefore, great concern should be raised about children's brief exposure to antibiotics if the results observed in mice are applicable to humans. Video Abstract.

Amino acid bites: Microbial snacking influences host metabolism.

The gut microbiota has the capacity to metabolize food-derived molecules. In this issue of Cell Host & Microbe, Li et al. explore how some bacterial species of the gut microbiota can deplete amino acids in the gut lumen, modulating the amino acid landscape and energy metabolism of the host.

Debugging neurodevelopment disorders.

Gut bacteria are thought to contribute to neurodevelopmental disorders, but whether they are causal or predictive of disease remains unclear. In a prospective longitudinal study of thousands of children, Ahrens et al. generate evidence for the role of the gut microbiome in neurodevelopmental disorders while highlighting important open questions.

Bacterial lifestyle shapes pangenomes.

Pangenomes vary across bacteria. Some species have fluid pangenomes, with a high proportion of genes varying between individual genomes. Other species have less fluid pangenomes, with different genomes tending to contain the same genes. Two main hypotheses have been suggested to explain this variation: differences in species' bacterial lifestyle and effective population size. However, previous studies have not been able to test between these hypotheses because the different features of lifestyle and effective population size are highly correlated with each other, and phylogenetically conserved, making it hard to disentangle their relative importance. We used phylogeny-based analyses, across 126 bacterial species, to tease apart the causal role of different factors. We found that pangenome fluidity was lower in i) host-associated compared with free-living species and ii) host-associated species that are obligately dependent on a host, live inside cells, and are more pathogenic and less motile. In contrast, we found no support for the competing hypothesis that larger effective population sizes lead to more fluid pangenomes. Effective population size appears to correlate with pangenome variation because it is also driven by bacterial lifestyle, rather than because of a causal relationship.

Isolation and characterization of pure cultures for metabolizing 1,4-dioxane in oligotrophic environments.

1,4-Dioxane concentration in most contaminated water is much less than 1 mg/L, which cannot sustain the growth of most reported 1,4-dioxane-metabolizing pure cultures. These pure cultures were isolated following enrichment of mixed cultures at high concentrations (20 to 1,000 mg/L). This study is based on a different strategy: 1,4-dioxane-metabolizing mixed cultures were enriched by periodically spiking 1,4-dioxane at low concentrations (≤1 mg/L). Five 1,4-dioxane-metabolizing pure strains LCD6B, LCD6D, WC10G, WCD6H, and WD4H were isolated and characterized. The partial 16S rRNA gene sequencing showed that the five bacterial strains were related to Dokdonella sp. (98.3%), Acinetobacter sp. (99.0%), Afipia sp. (99.2%), Nitrobacter sp. (97.9%), and Pseudonocardia sp. (99.4%), respectively. Nitrobacter sp. WCD6H is the first reported 1,4-dioxane-metabolizing bacterium in the genus of Nitrobacter. The net specific growth rates of these five cultures are consistently higher than those reported in the literature at 1,4-dioxane concentrations <0.5 mg/L. Compared to the literature, our newly discovered strains have lower half-maximum-rate concentrations (1.8 to 8.2 mg-dioxane/L), lower maximum specific 1,4-dioxane utilization rates (0.24 to 0.47 mg-dioxane/(mg-protein ⋅ d)), higher biomass yields (0.29 to 0.38 mg-protein/mg-dioxane), and lower decay coefficients (0.01 to 0.02 d-1). These are characteristics of microorganisms living in oligotrophic environments.

Metagenomic sequencing and reconstruction of 82 microbial genomes from barley seed communities.

Barley (Hordeum vulgare) is essential to global food systems and the brewing industry. Its physiological traits and microbial communities determine malt quality. Although microbes influence barley from seed health to fermentation, there is a gap in metagenomic insights during seed storage. Crucially, elucidating the changes in microbial composition associated with barley seeds is imperative for understanding how these fluctuations can impact seed health and ultimately, influence both agricultural yield and quality of barley-derived products. Whole metagenomes were sequenced from eight barley seed samples obtained at different storage time points from harvest to nine months. After binning, 82 metagenome-assembled genomes (MAGs) belonging to 26 distinct bacterial genera were assembled, with a substantial proportion of potential novel species. Most of our MAG dataset (61%) showed over 90% genome completeness. This pioneering barley seed microbial genome retrieval provides insights into species diversity and structure, laying the groundwork for understanding barley seed microbiome interactions at the genome level.

Molecular and phenotypic identification of bacterial species isolated from cows with mastitis from three regions of Poland.

BACKGROUND: Bovine mastitis is a widespread disease affecting dairy cattle worldwide and it generates substantial losses for dairy farmers. Mastitis may be caused by bacteria, fungi or algae. The most common species isolated from infected milk are, among others, Streptococcus spp., Escherichia coli, Staphylococcus aureus and non-aureus staphylococci and mammaliicocci. The aim of this paper is to determine the frequency of occurrence of bacterial species in milk samples from cows with mastitis from three regions of Poland: the north-east, the south-west and the south. To this end 203 milk samples taken from cows with a clinical form (CM) of mastitis (n = 100) and healthy animals (n = 103) were examined, which included culture on an appropriate medium followed by molecular detection of E. coli, S. aureus, Streptococcus agalactiae and Streptococcus uberis, as one of the most common species isolated from mastitis milk. RESULTS: The results obtained indicated that S. uberis was the most commonly cultivated CM species (38%, n = 38), followed by S. aureus (22%, n = 22), E. coli (21%, n = 21) and S. agalactiae (18%, n = 18). Similar frequencies in molecular methods were obtained for S. uberis (35.1%) and S. aureus (28.0%). The variation of sensitivity of both methods may be responsible for the differences in the E. coli (41.0%, p = 0.002) and S. agalactiae (5.0%, p = 0.004) detection rates. Significant differences in composition of species between three regions of Poland were noted for E. coli incidence (p < 0.001), in both the culture and molecular methods, but data obtained by the PCR method indicated that this species was the least common in north-eastern Poland, while the culture method showed that in north-eastern Poland E. coli was the most common species. Significant differences for the molecular method were also observed for S. uberis (p < 0.001) and S. aureus (p < 0.001). Both species were most common in southern and south-western Poland. CONCLUSIONS: The results obtained confirm the need to introduce rapid molecular tests for veterinary diagnostics, as well as providing important epidemiological data, to the best of our knowledge data on Polish cows in selected areas of Poland is lacking.

The species and abundance of gut bacteria both positively impact Phortica okadai behavior.

BACKGROUND: Gut bacteria, which serve as essential modulators, exert a significant impact on insect physiology and behavior and have substantial application potential in pest management. The dynamics of gut bacteria and their impact on Phortica okadai behavior remain unclear. METHODS: In this study, the dynamics of gut bacteria at different developmental stages in P. okadai were analyzed using 16S ribosomal RNA (rRNA) gene sequencing, and the species and abundance of gut bacteria that affect host behavior were examined via behavioral experiments. RESULTS: A total of 19 phyla, 29 classes, 74 orders, 101 species, and 169 genera were identified. The results of the behavioral experiments indicated that the species Lactiplantibacillus argentoratensis, Acetobacter tropicalis, Leuconostoc citreum, and Levilactobacillus brevis effectively influenced the feeding preference of P. okadai, and the single-bacterium-seeded P. okadai exhibited feeding preferences distinct from those of the germ-free (GF) and wild-type P. okadai. CONCLUSIONS: The species and relative abundance of gut bacteria together positively impact P. okadai behavior. Lactiplantibacillus argentoratensis, as the most attractive bacteria to P. okadai, presents opportunities for novel pest control strategies targeting this vector and agricultural pest.

Comparative analysis of midgut bacterial communities in Chikungunya virus-infected and non-infected Aedes aegypti Thai laboratory strain mosquitoes.

Chikungunya virus (CHIKV) poses a significant global health threat, re-emerging as a mosquito-transmitted pathogen that caused high fever, rash, and severe arthralgia. In Thailand, a notable CHIKV outbreak in 2019-2020 affected approximately 20,000 cases across 60 provinces, underscoring the need for effective mosquito control protocols. Previous studies have highlighted the role of midgut bacteria in the interaction between mosquito vectors and pathogen infections, demonstrating their ability to protect the insect from invading pathogens. However, research on the midgut bacteria of Aedes (Ae.) aegypti, the primary vector for CHIKV in Thailand remains limited. This study aims to characterize the bacterial communities in laboratory strains of Ae. aegypti, both infected and non-infected with CHIKV. Female mosquitoes from a laboratory strain of Ae. aegypti were exposed to a CHIKV-infected blood meal through membrane feeding, while the control group received a non-infected blood meal. At 7 days post-infection (dpi), mosquito midguts were dissected for 16S rRNA gene sequencing to identify midgut bacteria, and CHIKV presence was confirmed by E1-nested RT-PCR using mosquito carcasses. The study aimed to compare the bacterial communities between CHIKV-infected and non-infected groups. The analysis included 12 midgut bacterial samples, divided into three groups: CHIKV-infected (exposed and infected), non-infected (exposed but not infected), and non-exposed (negative control). Alpha diversity indices and Bray-Curtis dissimilarity matrix revealed significant differences in bacterial profiles among the three groups. The infected group exhibited an increased abundance of bacteria genus Gluconobacter, while Asaia was prevalent in both non-infected and negative control groups. Chryseobacterium was prominent in the negative control group. These findings highlight potential alterations in the distribution and abundance of gut microbiomes in response to CHIKV infection status. This study provides valuable insights into the dynamic relationship between midgut bacteria and CHIKV, underscoring the potential for alterations in bacterial composition depending on infection status. Understanding the relationships between mosquitoes and their microbiota holds promise for developing new methods and tools to enhance existing strategies for disease prevention and control. This research advances our understanding of the circulating bacterial composition, opening possibilities for new approaches in combating mosquito-borne diseases.

Ca(H2PO4)2 and MgSO4 activated nitrogen-related bacteria and genes in thermophilic stage of compost.

This study was conducted to investigate the effects of Ca(H2PO4)2 and MgSO4 on the bacterial community and nitrogen metabolism genes in the aerobic composting of pig manure. The experimental treatments were set up as control (C), 1% Ca(H2PO4)2 + 2% MgSO4 (CaPM1), and 1.5% Ca(H2PO4)2 + 3% MgSO4 (CaPM2), which were used at the end of composting for potting trials. The results showed that Ca(H2PO4)2 and MgSO4 played an excellent role in retaining nitrogen and increasing the alkali-hydrolyzed nitrogen (AN), available phosphorus (AP), and available potassium (AK) contents of the composts. Adding Ca(H2PO4)2 and MgSO4 changed the microbial community structure of the compost. The microorganisms associated with nitrogen retention were activated. The complexity of the microbial network was enhanced. Genetic prediction analysis showed that the addition of Ca(H2PO4)2 and MgSO4 reduced the accumulation of nitroso-nitrogen and the process of denitrification. At the same time, despite the reduction of genes related to nitrogen fixation, the conversion of ammonia to nitrogenous organic compounds was promoted and the stability of nitrogen was increased. Mantel test analysis showed that Ca(H2PO4)2 and MgSO4 can affect nitrogen transformation-related bacteria and thus indirectly affect nitrogen metabolism genes by influencing the temperature, pH, and organic matter (OM) of the compost and also directly affected nitrogen metabolism genes through PO43- and Mg2+. The pot experiment showed that composting with 1.5% Ca(H2PO4)2 + 3% MgSO4 produced the compost product that improved the growth yield and nutrient content of cilantro and increased the fertility of the soil. In conclusion, Ca(H2PO4)2 and MgSO4 reduces the loss of nitrogen from compost, activates nitrogen-related bacteria and genes in the thermophilic phase of composting, and improves the fertilizer efficiency of compost products. KEY POINTS: • Ca(H2PO4)2 and MgSO4 reduced the nitrogen loss and improved the compost effect • Activated nitrogen-related bacteria and altered nitrogen metabolism genes • Improved the yield and quality of cilantro and fertility of soil.

Gut microbiota composition in travellers is associated with faecal lipocalin-2, a mediator of gut inflammation.

Introduction: We examined the gut microbiota of travellers returning from tropical areas with and without traveller's diarrhoea (TD) and its association with faecal lipocalin-2 (LCN2) levels. Methods: Participants were recruited at the Hospital Clinic of Barcelona, Spain, and a single stool sample was collected from each individual to perform the diagnostic of the etiological agent causing gastrointestinal symptoms as well as to measure levels of faecal LCN2 as a biomarker of gut inflammation. We also characterised the composition of the gut microbiota by sequencing the region V3-V4 from the 16S rRNA gene, and assessed its relation with the clinical presentation of TD and LCN2 levels using a combination of conventional statistical tests and unsupervised machine learning approaches. Results: Among 61 participants, 45 had TD, with 40% having identifiable etiological agents. Surprisingly, LCN2 levels were similar across groups, suggesting gut inflammation occurs without clinical TD symptoms. Differential abundance (DA) testing highlighted a microbial profile tied to high LCN2 levels, marked by increased Proteobacteria and Escherichia-Shigella, and decreased Firmicutes, notably Oscillospiraceae. UMAP analysis confirmed this profile's association, revealing distinct clusters based on LCN2 levels. The study underscores the discriminatory power of UMAP in capturing meaningful microbial patterns related to clinical variables. No relevant differences in the gut microbiota composition were found between travellers with or without TD. Discussion: The findings suggest a correlation between gut microbiome and LCN2 levels during travel, emphasising the need for further research to discern the nature of this relationship.

Loss to gain: pseudogenes in microorganisms, focusing on eubacteria, and their biological significance.

Pseudogenes are defined as "non-functional" copies of corresponding parent genes. The cognition of pseudogenes continues to be refreshed through accumulating and updating research findings. Previous studies have predominantly focused on mammals, but pseudogenes have received relatively less attention in the field of microbiology. Given the increasing recognition on the importance of pseudogenes, in this review, we focus on several aspects of microorganism pseudogenes, including their classification and characteristics, their generation and fate, their identification, their abundance and distribution, their impact on virulence, their ability to recombine with functional genes, the extent to which some pseudogenes are transcribed and translated, and the relationship between pseudogenes and viruses. By summarizing and organizing the latest research progress, this review will provide a comprehensive perspective and improved understanding on pseudogenes in microorganisms. KEY POINTS: • Concept, classification and characteristics, identification and databases, content, and distribution of microbial pseudogenes are presented. • How pseudogenization contribute to pathogen virulence is highlighted. • Pseudogenes with potential functions in microorganisms are discussed.

Incidence of resistance to ALS and ACCase inhibitors in Echinochloa species and soil microbial composition in Northern Italy.

The increasing amount of weeds surviving herbicide represents a very serious problem for crop management. The interaction between microbial community of soil and herbicide resistance, along with the potential evolutive consequences, are still poorly known and need to be investigated to better understand the impact on agricultural management. In our study, we analyzed the microbial composition of soils in 32 farms, located in the Northern Italy rice-growing area (Lombardy) with the aim to evaluate the relationship between the microbial composition and the incidence of resistance to acetolactate synthase (ALS) and acetyl-CoA carboxylase (ACCase) inhibiting herbicides in Echinochloa species. We observed that the coverage of weeds survived herbicide treatment was higher than 60% in paddy fields with a low microbial biodiversity and less than 5% in those with a high microbial biodiversity. Fungal communities showed a greater reduction in richness than Bacteria. In soils with a reduced microbial diversity, a significant increase of some bacterial and fungal orders (i.e. Lactobacillales, Malasseziales and Diaporthales) was observed. Interestingly, we identified two different microbial profiles linked to the two conditions: high incidence of herbicide resistance (H-HeR) and low incidence of herbicide resistance (L-HeR). Overall, the results we obtained allow us to make hypotheses on the greater or lesser probability of herbicide resistance occurrence based on the composition of the soil microbiome and especially on the degree of biodiversity of the microbial communities.

Characterizing the blood microbiota in healthy and febrile domestic cats via 16s rRNA sequencing.

This study aimed to evaluate the blood bacterial microbiota in healthy and febrile cats. High-quality sequencing reads from the 16S rRNA gene variable region V3-V4 were obtained from genomic blood DNA belonging to 145 healthy cats, and 140 febrile cats. Comparisons between the blood microbiota of healthy and febrile cats revealed dominant presence of Actinobacteria, followed by Firmicutes and Proteobacteria, and a lower relative abundance of Bacteroidetes. Upon lower taxonomic levels, the bacterial composition was significantly different between healthy and febrile cats. The families Faecalibacterium and Kineothrix (Firmicutes), and Phyllobacterium (Proteobacteria) experienced increased abundance in febrile samples. Whereas Thioprofundum (Proteobacteria) demonstrated a significant decrease in abundance in febrile. The bacterial composition and beta diversity within febrile cats was different according to the affected body system (Oral/GI, systemic, skin, and respiratory) at both family and genus levels. Sex and age were not significant factors affecting the blood microbiota of febrile cats nor healthy ones. Age was different between young adult and mature adult healthy cats. Alpha diversity was unaffected by any factors. Overall, the findings suggest that age, health status and nature of disease are significant factors affecting blood microbiota diversity and composition in cats, but sex is not.

Insights into phage-bacteria interaction in cold seep Gigantidas platifrons through metagenomics and transcriptome analyses.

Viruses are crucial for regulating deep-sea microbial communities and biogeochemical cycles. However, their roles are still less characterized in deep-sea holobionts. Bathymodioline mussels are endemic species inhabiting cold seeps and harboring endosymbionts in gill epithelial cells for nutrition. This study unveiled a diverse array of viruses in the gill tissues of Gigantidas platifrons mussels and analyzed the viral metagenome and transcriptome from the gill tissues of Gigantidas platifrons mussels collected from a cold seep in the South Sea. The mussel gills contained various viruses including Baculoviridae, Rountreeviridae, Myoviridae and Siphovirdae, but the active viromes were Myoviridae, Siphoviridae, and Podoviridae belonging to the order Caudovirales. The overall viral community structure showed significant variation among environments with different methane concentrations. Transcriptome analysis indicated high expression of viral structural genes, integrase, and restriction endonuclease genes in a high methane concentration environment, suggesting frequent virus infection and replication. Furthermore, two viruses (GP-phage-contig14 and GP-phage-contig72) interacted with Gigantidas platifrons methanotrophic gill symbionts (bathymodiolin mussels host intracellular methanotrophic Gammaproteobacteria in their gills), showing high expression levels, and have huge different expression in different methane concentrations. Additionally, single-stranded DNA viruses may play a potential auxiliary role in the virus-host interaction using indirect bioinformatics methods. Moreover, the Cro and DNA methylase genes had phylogenetic similarity between the virus and Gigantidas platifrons methanotrophic gill symbionts. This study also explored a variety of viruses in the gill tissues of Gigantidas platifrons and revealed that bacteria interacted with the viruses during the symbiosis with Gigantidas platifrons. This study provides fundamental insights into the interplay of microorganisms within Gigantidas platifrons mussels in deep sea.

Metagenomic evaluation of peanut rhizosphere microbiome from the farms of Saurashtra regions of Gujarat, India.

The narrow zone of soil around the plant roots with maximum microbial activity termed as rhizosphere. Rhizospheric bacteria promote the plant growth directly or indirectly by providing the nutrients and producing antimicrobial compounds. In this study, the rhizospheric microbiota of peanut plants was characterized from different farms using an Illumina-based partial 16S rRNA gene sequencing to evaluate microbial diversity and identify the core microbiome through culture-independent (CI) approach. Further, all rhizospheric bacteria that could grow on various nutrient media were identified, and the diversity of those microbes through culture-dependent method (CD) was then directly compared with their CI counterparts. The microbial population profiles showed a significant correlation with organic carbon and concentration of phosphate, manganese, and potassium in the rhizospheric soil. Genera like Sphingomicrobium, Actinoplanes, Aureimonas _A, Chryseobacterium, members from Sphingomonadaceae, Burkholderiaceae, Pseudomonadaceae, Enterobacteriaceae family, and Bacilli class were found in the core microbiome of peanut plants. As expected, the current study demonstrated more bacterial diversity in the CI method. However, a higher number of sequence variants were exclusively present in the CD approach compared to the number of sequence variants shared between both approaches. These CD-exclusive variants belonged to organisms that are more typically found in soil. Overall, this study portrayed the changes in the rhizospheric microbiota of peanuts in different rhizospheric soil and environmental conditions and gave an idea about core microbiome of peanut plant and comparative bacterial diversity identified through both approaches.

Environmental specificity of karst cave habitats evidenced by diverse symbiotic bacteria in Opiliones.

BACKGROUND: Karst caves serve as natural laboratories, providing organisms with extreme and constant conditions that promote isolation, resulting in a genetic relationship and living environment that is significantly different from those outside the cave. However, research on cave creatures, especially Opiliones, remains scarce, with most studies focused on water, soil, and cave sediments. RESULTS: The structure of symbiotic bacteria in different caves were compared, revealing significant differences. Based on the alpha and beta diversity, symbiotic bacteria abundance and diversity in the cave were similar, but the structure of symbiotic bacteria differed inside and outside the cave. Microorganisms in the cave play an important role in material cycling and energy flow, particularly in the nitrogen cycle. Although microbial diversity varies inside and outside the cave, Opiliones in Beijing caves and Hainan Island exhibited a strong similarity, indicating that the two environments share commonalities. CONCLUSIONS: The karst cave environment possesses high microbial diversity and there are noticeable differences among different caves. Different habitats lead to significant differences in the symbiotic bacteria in Opiliones inside and outside the cave, and cave microorganisms have made efforts to adapt to extreme environments. The similarity in symbiotic bacteria community structure suggests a potential similarity in host environments, providing an explanation for the appearance of Sinonychia martensi in caves in the north.

Arbuscular mycorrhizal fungi and Streptomyces: brothers in arms to shape the structure and function of the hyphosphere microbiome in the early stage of interaction.

BACKGROUND: Fungi and bacteria coexist in a wide variety of environments, and their interactions are now recognized as the norm in most agroecosystems. These microbial communities harbor keystone taxa, which facilitate connectivity between fungal and bacterial communities, influencing their composition and functions. The roots of most plants are associated with arbuscular mycorrhizal (AM) fungi, which develop dense networks of hyphae in the soil. The surface of these hyphae (called the hyphosphere) is the region where multiple interactions with microbial communities can occur, e.g., exchanging or responding to each other's metabolites. However, the presence and importance of keystone taxa in the AM fungal hyphosphere remain largely unknown. RESULTS: Here, we used in vitro and pot cultivation systems of AM fungi to investigate whether certain keystone bacteria were able to shape the microbial communities growing in the hyphosphere and potentially improved the fitness of the AM fungal host. Based on various AM fungi, soil leachates, and synthetic microbial communities, we found that under organic phosphorus (P) conditions, AM fungi could selectively recruit bacteria that enhanced their P nutrition and competed with less P-mobilizing bacteria. Specifically, we observed a privileged interaction between the isolate Streptomyces sp. D1 and AM fungi of the genus Rhizophagus, where (1) the carbon compounds exuded by the fungus were acquired by the bacterium which could mineralize organic P and (2) the in vitro culturable bacterial community residing on the surface of hyphae was in part regulated by Streptomyces sp. D1, primarily by inhibiting the bacteria with weak P-mineralizing ability, thereby enhancing AM fungi to acquire P. CONCLUSIONS: This work highlights the multi-functionality of the keystone bacteria Streptomyces sp. D1 in fungal-bacteria and bacterial-bacterial interactions at the hyphal surface of AM fungi. Video Abstract.

Viruses contribute to microbial diversification in the rumen ecosystem and are associated with certain animal production traits.

BACKGROUND: The rumen microbiome enables ruminants to digest otherwise indigestible feedstuffs, thereby facilitating the production of high-quality protein, albeit with suboptimal efficiency and producing methane. Despite extensive research delineating associations between the rumen microbiome and ruminant production traits, the functional roles of the pervasive and diverse rumen virome remain to be determined. RESULTS: Leveraging a recent comprehensive rumen virome database, this study analyzes virus-microbe linkages, at both species and strain levels, across 551 rumen metagenomes, elucidating patterns of microbial and viral diversity, co-occurrence, and virus-microbe interactions. Additionally, this study assesses the potential role of rumen viruses in microbial diversification by analyzing prophages found in rumen metagenome-assembled genomes. Employing CRISPR-Cas spacer-based matching and virus-microbe co-occurrence network analysis, this study suggests that the viruses in the rumen may regulate microbes at strain and community levels through both antagonistic and mutualistic interactions. Moreover, this study establishes that the rumen virome demonstrates responsiveness to dietary shifts and associations with key animal production traits, including feed efficiency, lactation performance, weight gain, and methane emissions. CONCLUSIONS: These findings provide a substantive framework for further investigations to unravel the functional roles of the virome in the rumen in shaping the microbiome and influencing overall animal production performance. Video Abstract.

ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences.

BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identification of ARGs, particularly from high-throughput sequencing data of the specimens, is the state-of-the-art method for comprehensively monitoring their spread and evolution. Current computational methods to identify ARGs mainly rely on alignment-based sequence similarities with known ARGs. Such approaches are limited by choice of reference databases and may potentially miss novel ARGs. The similarity thresholds are usually simple and could not accommodate variations across different gene families and regions. It is also difficult to scale up when sequence data are increasing. RESULTS: In this study, we developed ARGNet, a deep neural network that incorporates an unsupervised learning autoencoder model to identify ARGs and a multiclass classification convolutional neural network to classify ARGs that do not depend on sequence alignment. This approach enables a more efficient discovery of both known and novel ARGs. ARGNet accepts both amino acid and nucleotide sequences of variable lengths, from partial (30-50 aa; 100-150 nt) sequences to full-length protein or genes, allowing its application in both target sequencing and metagenomic sequencing. Our performance evaluation showed that ARGNet outperformed other deep learning models including DeepARG and HMD-ARG in most of the application scenarios especially quasi-negative test and the analysis of prediction consistency with phylogenetic tree. ARGNet has a reduced inference runtime by up to 57% relative to DeepARG. CONCLUSIONS: ARGNet is flexible, efficient, and accurate at predicting a broad range of ARGs from the sequencing data. ARGNet is freely available at https://github.com/id-bioinfo/ARGNet , with an online service provided at https://ARGNet.hku.hk . Video Abstract.