Antibiotic resistance is a worldwide problem that imposes a devastating effect on developing countries and requires immediate interventions. Initially, most of the antibiotic drugs were identified by culturing soil microbes. However, this method is prone to discovering the same antibiotics repeatedly. The present study employed a shotgun metagenomics approach to investigate the taxonomic diversity, functional potential, and biosynthetic capacity of microbiomes from two natural agricultural farmlands located in Bekeka and Welmera Choke Kebelle in Ethiopia for the first time. Analysis of the small subunit rRNA revealed bacterial domain accounting for 83.33% and 87.24% in the two selected natural farmlands. Additionally, the analysis showed the dominance of Proteobacteria representing 27.27% and 28.79% followed by Actinobacteria making up 12.73% and 13.64% of the phyla composition. Furthermore, the analysis revealed the presence of unassigned bacteria in the studied samples. The metagenome functional analysis showed 176,961 and 104, 636 number of protein-coding sequences (pCDS) from the two samples found a match with 172,655 and 102, 275 numbers of InterPro entries, respectively. The Genome ontology annotation suggests the presence of 5517 and 3293 pCDS assigned to the \"biosynthesis process\". Numerous Kyoto Encyclopedia of Genes and Genomes modules (KEGG modules) involved in the biosynthesis of terpenoids and polyketides were identified. Furthermore, both known and novel Biosynthetic gene clusters, responsible for the production of secondary metabolites, such as polyketide synthases, non-ribosomal peptide synthetase, ribosomally synthesized and post-translationally modified peptides (Ripp), and Terpene, were discovered. Generally, from the results it can be concluded that the microbiomes in the selected sampling sites have a hidden functional potential for the biosynthesis of secondary metabolites. Overall, this study can serve as a strong preliminary step in the long journey of bringing new antibiotics to the market.

Arid regions harbor seasonal and permanent wetlands, as biodiversity hotspots crucial for ecosystem services despite harsh conditions. These wetlands, typically dependent on episodic intense rainfall, are understudied compared to their humid counterparts. While the diversity of plants and animals in these wetlands is well-known, the microbial communities remain largely unexplored. To address this knowledge gap, we employed metagenome sequencing technologies to profile protist communities, including pathogenic protozoa, and their associated functional pathways, in sediment of permanent and seasonal arid freshwater wetlands across northern South Africa. Results revealed a core community of protists dominated by phylum Apicomplexa (66.73 %), Euglenazoa (19.03 %), Bacillariophyta (5.44 %), Metamonada (4.65 %), Cryptophyta (1.90 %), and Amoebazoa (1.21 %). Seasonal wetlands showed significantly higher protist diversity compared to permanent wetlands (Shannon index, p = 0.019; Chao1, p = 0.0095). A high abundance and diversity of human and zoonotic pathogenic protists (87.67 %) was observed, with lower levels of photoautotrophs (6.69 %) and limited diversity of phagotrophs (5.64 %). Key photoautotrophs identified included diatoms (Thalassiosiraceae and Phaeodactylaceae) and cryptophytes (genus Hemiselmis and Cryptophyta), with consumers/phagotrophs exhibited a correlation with the bacterial community abundance (r2 = 0.218, p < 0.001). Pathogenic protozoans identified, include malaria-causing Plasmodium, kinetoplastids (genus Besnoita, Theilleria, Neospora, Toxoplasma, Encephalitozoon, and Babesia) and waterborne protozoans of public health importance (such as Cryptosporidium parvum and Giardia lamblia). Furthermore, the enrichment of pathogenesis-associated pathways (amino acid biosynthesis, peptidoglycan maturation, heme biosynthesis and degradation, and the Calvin-Benson-Bassham cycle), along with virulence gene families identified, highlighted these wetlands as potential reservoirs for infectious diseases. Our results unveil a baseline protist taxonomic and functional composition within arid wetlands, including beneficial and pathogenic protozoa. The close proximity of these wetlands to human activity raises concern for local and transboundary spread of these pathogens. Thus, continued monitoring is vital for disease control and preserving these unique ecosystems.

BACKGROUND: Respiratory viruses significantly impact global morbidity and mortality, causing more disease in humans than any other infectious agent. Beyond pathogens, various viruses and bacteria colonize the respiratory tract without causing disease, potentially influencing respiratory diseases\' pathogenesis. Nevertheless, our understanding of respiratory microbiota is limited by technical constraints, predominantly focusing on bacteria and neglecting crucial populations like viruses. Despite recent efforts to improve our understanding of viral diversity in the human body, our knowledge of viral diversity associated with the human respiratory tract remains limited.
METHODS: Following a comprehensive search in bibliographic and sequencing data repositories using keyword terms, we retrieved shotgun metagenomic data from public repositories (n = 85). After manual curation, sequencing data files from 43 studies were analyzed using EVEREST (pipEline for Viral assEmbly and chaRactEriSaTion). Complete and high-quality contigs were further assessed for genomic and taxonomic characterization.
RESULTS: Viral contigs were obtained from 194 out of the 868 FASTQ files processed through EVEREST. Of the 1842 contigs that were quality assessed, 8% (n = 146) were classified as complete/high-quality genomes. Most of the identified viral contigs were taxonomically classified as bacteriophages, with taxonomic resolution ranging from the superkingdom level down to the species level. Captured contigs were spread across 25 putative families and varied between RNA and DNA viruses, including previously uncharacterized viral genomes. Of note, airway samples also contained virus(es) characteristic of the human gastrointestinal tract, which have not been previously described as part of the lung virome. Additionally, by performing a meta-analysis of the integrated datasets, ecological trends within viral populations linked to human disease states and their biogeographical distribution along the respiratory tract were observed.
CONCLUSIONS: By leveraging publicly available repositories of shotgun metagenomic data, the present study provides new insights into viral genomes associated with specimens from the human respiratory tract across different disease spectra. Further studies are required to validate our findings and evaluate the potential impact of these viral communities on respiratory tract physiology.

Paired-end short reads of Illumina HiSeq, MiSeq, and NovaSeq of simulated bacterial communities from fresh spinach and surface water were generated in silico at various sequencing depths. Multidrug-resistant Salmonella enterica serotype Indiana was included in the spinach community, while the water community contained multidrug-resistant Pseudomonas aeruginosa.

BACKGROUND: People living with HIV (PLWH) are at increased risk of acquisition of multidrug resistant organisms due to higher rates of predisposing factors. The gut microbiome is the main reservoir of the collection of antimicrobial resistance determinants known as the gut resistome. In PLWH, changes in gut microbiome have been linked to immune activation and HIV-1 associated complications. Specifically, gut dysbiosis defined by low microbial gene richness has been linked to low Nadir CD4 + T-cell counts. Additionally, sexual preference has been shown to strongly influence gut microbiome composition in PLWH resulting in different Prevotella or Bacteroides enriched enterotypes, in MSM (men-who-have-sex-with-men) or no-MSM, respectively. To date, little is known about gut resistome composition in PLWH due to the scarcity of studies using shotgun metagenomics. The present study aimed to detect associations between different microbiome features linked to HIV-1 infection and gut resistome composition.
RESULTS: Using shotgun metagenomics we characterized the gut resistome composition of 129 HIV-1 infected subjects showing different HIV clinical profiles and 27 HIV-1 negative controls from a cross-sectional observational study conducted in Barcelona, Spain. Most no-MSM showed a Bacteroides-enriched enterotype and low microbial gene richness microbiomes. We did not identify differences in resistome diversity and composition according to HIV-1 infection or immune status. However, gut resistome was more diverse in MSM group, Prevotella-enriched enterotype and gut micorbiomes with high microbial gene richness compared to no-MSM group, Bacteroides-enriched enterotype and gut microbiomes with low microbial gene richness. Additionally, gut resistome beta-diversity was different according to the defined groups and we identified a set of differentially abundant antimicrobial resistance determinants based on the established categories.
CONCLUSIONS: Our findings reveal a significant correlation between gut resistome composition and various host variables commonly associated with gut microbiome, including microbiome enterotype, microbial gene richness, and sexual preference. These host variables have been previously linked to immune activation and lower Nadir CD4 + T-Cell counts, which are prognostic factors of HIV-related comorbidities. This study provides new insights into the relationship between antibiotic resistance and clinical characteristics of PLWH.

We previously demonstrated that mice carrying natural mtDNA variants of the FVB/NJ strain (m.7778 G>T in the mt-Atp8 gene in mitochondrial complex V), namely C57BL/6 J-mtFVB/NJ (B6-mtFVB), exhibited (i) partial protection from experimental skin inflammatory diseases in an anti-murine type VII collagen antibody-induced skin inflammation model and psoriasiform dermatitis model; (ii) significantly altered metabolites, including short-chain fatty acids, according to targeted metabolomics of liver, skin and lymph node samples; and (iii) a differential composition of the gut microbiota according to bacterial 16 S rRNA gene sequencing of stool samples compared to wild-type C57BL/6 J (B6) mice. To further dissect these disease-contributing factors, we induced an experimental antibody-induced skin inflammatory disease in gnotobiotic mice. We performed shotgun metagenomic sequencing of caecum contents and untargeted metabolomics of liver, CD4+ T cell, and caecum content samples from conventional B6-mtFVB and B6 mice. We identified D-glucosamine as a candidate mediator that ameliorated disease severity in experimental antibody-induced skin inflammation by modulating immune cell function in T cells, neutrophils and macrophages. Because mice carrying mtDNA variants of the FVB/NJ strain show differential disease susceptibility to a wide range of experimental diseases, including diet-induced atherosclerosis in low-density lipoprotein receptor knockout mice and collagen antibody-induced arthritis in DBA/1 J mice, this experimental approach is valuable for identifying novel therapeutic options for skin inflammatory conditions and other chronic inflammatory diseases to which mice carrying specific mtDNA variants show differential susceptibility.

Shotgun metagenomics sequencing experiments are finding a wide range of applications. Nonetheless, there are still limited guidelines regarding the number of sequences needed to acquire meaningful information for taxonomic profiling and antimicrobial resistance gene (ARG) identification. In this study, we explored this issue in the context of oral microbiota by sequencing with a very high number of sequences (~ 100 million), four human plaque samples, and one microbial community standard and by evaluating the performance of microbial identification and ARGs detection through a downsampling procedure. When investigating the impact of a decreasing number of sequences on quantitative taxonomic profiling in the microbial community standard datasets, we found some discrepancies in the identified microbial species and their abundances when compared to the expected ones. Such differences were consistent throughout downsampling, suggesting their link to taxonomic profiling methods limitations. Overall, results showed that the number of sequences has a great impact on metagenomic samples at the qualitative (i.e., presence/absence) level in terms of loss of information, especially in experiments having less than 40 million reads, whereas abundance estimation was minimally affected, with only slight variations observed in low-abundance species. The presence of ARGs was also assessed: a total of 133 ARGs were identified. Notably, 23% of them inconsistently resulted as present or absent across downsampling datasets of the same sample. Moreover, over half of ARGs were lost in datasets having less than 20 million reads. This study highlights the importance of carefully considering sequencing aspects and suggests some guidelines for designing shotgun metagenomics experiments with the final goal of maximizing oral microbiome analyses. Our findings suggest varying optimized sequence numbers according to different study aims: 40 million for microbiota profiling, 50 million for low-abundance species detection, and 20 million for ARG identification. KEY POINTS: • Forty million sequences are a cost-efficient solution for microbiota profiling • Fifty million sequences allow low-abundance species detection • Twenty million sequences are recommended for ARG identification.

Microbes play a significant role in the cleanup of xenobiotic contaminants. Based on metagenomes derived from long-term enrichment cultures grown on xenobiotic solvents, we report 166 metagenome-assembled genomes, of which 137 are predicted to be more than 90% complete. These genomes broaden the representation of xenobiotic degraders.

The exploitation of exciting features of plastics for diverse applications has resulted in significant plastic waste generation, which negatively impacts environmental compartments, metabolic processes, and the well-being of aquatic ecosystems biota. A shotgun metagenomic approach was deployed to investigate the microbial consortia, degradation pathways, and enzyme systems involved in the degradation of plastics in a tropical lentic pond sediment (APS). Functional annotation of the APS proteome (ORFs) using the PlasticDB database revealed annotation of 1015 proteins of enzymes such as depolymerase, esterase, lipase, hydrolase, nitrobenzylesterase, chitinase, carboxylesterase, polyesterase, oxidoreductase, polyamidase, PETase, MHETase, laccase, alkane monooxygenase, among others involved in the depolymerization of the plastic polymers. It also revealed that polyethylene glycol (PEG), polyhydroxyalkanoates (PHA), polyhydroxybutyrate (PHB), polylactic acid (PLA), polybutylene adipate terephthalate (PBAT), polyethylene terephthalate (PET), and nylon have the highest number of annotated enzymes. Further annotation using the KEGG GhostKOALA revealed that except for terephthalate, all the other degradation products of the plastic polymers depolymerization such as glyoxylate, adipate, succinate, 1,4-butanediol, ethylene glycol, lactate, and acetaldehyde were further metabolized to intermediates of the tricarboxylic acid cycle. Taxonomic characterization of the annotated proteins using the AAI Profiler and BLASTP revealed that Pseudomonadota members dominate most plastic types, followed by Actinomycetota and Acidobacteriota. The study reveals novel plastic degraders from diverse phyla hitherto not reported to be involved in plastic degradation. This suggests that plastic pollution in aquatic environments is prevalent with well-adapted degrading communities and could be the silver lining in mitigating the impacts of plastic pollution in aquatic environments.

Sfela is a white brined Greek cheese of protected designation of origin (PDO) produced in the Peloponnese region from ovine, caprine milk, or a mixture of the two. Despite the PDO status of Sfela, very few studies have addressed its properties, including its microbiology. For this reason, we decided to investigate the microbiome of two PDO industrial Sfela cheese samples along with two non-PDO variants, namely Sfela touloumotiri and Xerosfeli. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS), 16S rDNA amplicon sequencing and shotgun metagenomics analysis were used to identify the microbiome of these traditional cheeses. Cultured-based analysis showed that the most frequent species that could be isolated from Sfela cheese were Enterococcus faecium, Lactiplantibacillus plantarum, Levilactobacillus brevis, Pediococcus pentosaceus and Streptococcus thermophilus. Shotgun analysis suggested that in industrial Sfela 1, Str. thermophilus dominated, while industrial Sfela 2 contained high levels of Lactococcus lactis. The two artisanal samples, Sfela touloumotiri and Xerosfeli, were dominated by Tetragenococcus halophilus and Str. thermophilus, respectively. Debaryomyces hansenii was the only yeast species with abundance > 1% present exclusively in the Sfela touloumotiri sample. Identifying additional yeast species in the shotgun data was challenging, possibly due to their low abundance. Sfela cheese appears to contain a rather complex microbial ecosystem and thus needs to be further studied and understood. This might be crucial for improving and standardizing both its production and safety measures.