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Background:. In the dynamic progression of root canal infections, the resultant change in environmental conditions directs the adaptation of the microbiome in terms of richness, evenness, and diversity. Objective:. The goal of this study is to contrast the interradicular bacterial community structures of teeth in acute and chronic stages and investigate potential microorganisms associated with persistent apical periapical infections. Methods:. Interradicular samples were collected from 10 teeth in the apical periodontitis group and 10 teeth in the chronic apical periodontitis group. High-throughput next-generation sequencing (NGS)–based microbial identification through the Illumina platform was used to characterize the complex intraradicular microbial communities in acute and chronic root canal infections. Results:. Bacteria were the major domain, with a prevalence of >97% (acute cases: 98.11% and chronic cases: 97.6%) compared to eukaryotes and archaea. Bacterial diversity was relatively higher in acute compared to chronic conditions under 10 and 9 phyla, 79 and 64 genera, and 172 and 135 species, respectively. These endodontically infecting bacteria belonged to Firmicutes (47.21%), Bacteroidetes (20.07%), and Proteobacteria (10.72%) in acute conditions, while in the chronic stage, Firmicutes (40.85%), Proteobacteria (27.80%), and Actinobacteria (14.79%) were abundant. The phylum Candidatus Saccharibacteria was exclusively found in acute samples. Spirochaetes and Synergistetes were found predominantly in acute infections compared to chronic infections. Bacillus and Lactobacillus were found in equal and highest abundance under the phylum Firmicutes in both conditions. Conclusion:. This study provides information on the differential microbial community present in the apical root canal system of teeth with acute and chronic apical periodontitis and contributes to new approaches or channels for future research on preventive measures and therapeutic protocols during disease progression and treatment. However, functional characterization and detection of antimicrobial resistance in these two clinical conditions can supplement these findings for deciding routine drug treatment for periodontal infections.

The river Ganges in India has faced considerable issues due to water quality degradation caused by various anthropogenic activities. This study employs metagenomic analysis to comprehensively characterize bacterial communities, explore functional genomics, and investigate the prevalence of virulence factors and antibiotic resistant genes (ARGs) within the sediment environment of the river Ganges. Taxonomic profiling revealed that Proteobacteria were the most dominating phyla found in all samples, whereas the abundance of Pseudomonas at the genus level was the highest in all the samples. Functional annotation and pathway analysis uncover the genomic potential of sediment associated bacteria, shedding light on metabolic pathways, biogeochemical processes, human diseases and adaptive mechanisms within the riverine ecosystem. Moreover, identifying the highest number of genes related to virulence factors was observed in K1 samples (3), and the highest number of genes related to ARGs found in K3 (25) samples emphasizes the need to understand potential pathogenicity in these environments. Characterization of ARGs provides crucial insights into the prevalence of resistance determinants, their genetic contexts, and potential sources of antibiotic resistance in this vital aquatic ecosystem. Overall metagenomics analysis in different sampling sites of river Ganga observed nearly the same OTUs at microbial communities at the taxonomic level but not at a functional level. This research can be a critical foundation for assessing the ecological implications of microbial communities, functional genomics, and the resistome in the river Ganges sediments. The findings underscore the importance of metagenomic approaches in elucidating the intricate microbial ecology and the prevalence of genetic elements relevant to environmental health and antimicrobial resistance in aquatic ecosystems. Further investigation would be required to understand the underlying cause behind the restoration of microbial functional profiles, including ARGs and VFs, to unravel the rejuvenation aspects of this unique ecosystem.

Plastic waste has become a significant global ecological concern due to its substantial harmful impacts. They are eventually colonized and transformed by diverse microbial communities known as the ‘‘plastisphere”. Only a limited group of microbes have been identified so far due to the prevalence of non-culturable strains that inhabit polymer substrates. We investigated the community diversity and predictive functionality of the plastisphere microbiota using a high-throughput next-generation sequencing (NGS) approach to unveil their plastic degrading potential. Samples were collected from four different plastic-enriched disposal sites adjacent to Kolkata, West Bengal, India, followed by processing, gDNA extraction, library preparation, and sequencing. The most prevalent phyla were Proteobacteria, followed by Bacteroidetes, Actinobacteria, Cyanobacteria, Firmicutes, and Verrucomicrobia. The functional profiling revealed that genes associated with metabolism, cellular processes, and signalling were most prevalent, followed by poorly characterized information storage and processing. In this study, we predicted the existence of a beneficial microbiome associated with bioremediation and plastic degradation, which suggests the potential utilization of plastics as primary carbon sources. Our findings also highlighted the existence of promising microbial enzymes associated with the biodegradation of several plastic substrates.Furthermore, our research unveiled the enriched distribution of beneficial microbiome in the studied metagenome, which offers a diverse prospect. This investigation establishes a connection between the structure of microbial communities and diverse genes actively engaged in the biodegradation of plastic waste within plastic disposal sites. These beneficial degraders can be investigated further for broad-spectrum applications in plastic bioremediation. Subsequent explorations of their plastic degrading enzymes will provide profound contributions to plastic pollution mitigation.

Geothermally heated spring water contaminated with decomposed leaf biomass creates unique hot spring ecosystems that support the recycling of diverse nutrients and harbor microbial consortia capable of degrading lignocellulose. We present microbiome and transcriptome data from the bacterial consortium of Deulajhari hot springs, characterized by a temperature of approximately 58 °C and surrounded by a dense population of pandanus plants in Angul, Odisha, India. Metagenomics and metatranscriptomics datasets were generated by extracting total DNA and RNA from the consortium sample of hotspring sediment, followed by shotgun sequencing using the Illumina HiSeq 2500 platform. The metagenomics dataset produced approximately 38,694 contigs, while the metatranscriptomics dataset yielded 9226 contigs, resulting in a total nucleotide size of 89,857,616 and 15,541,403 bps, respectively. Analysis using MEGAN6 against the NCBI “taxonomy” database revealed the presence of 18 and 12 phyla, including candidate phyla, in respective datasets. Proteobacteria exhibited the highest relative abundance in the metagenomics dataset, while Firmicutes was highly abundant in the metatranscriptomics dataset. At the genus level, a total of 92 and 25 genera were predicted in both datasets, with lignocellulose degrading Meiothermus being highly abundant in both metagenomics and metatranscriptomics datasets. We also observed that the unknown bacteria and unidentified sequences were found in significant proportion in the metatranscriptomics dataset. We assembled and functionally annotated approximately 23,960 contigs using the Prokka pipeline. Among the SEED category, the most expressed and annotated microbial genes fall under the unknown category as well as Biotin synthesis and their utilization. Furthermore, some of these genes were implicated in the degradation of aromatic amino acids, D-mannitol, and D-mannose. These findings contribute to our understanding of how the composition and abundance of bacterial communities facilitate lignocellulose degradation in extreme environments and biofuel generation.

Hot springs are the reservoirs of novel hyperthermophilic and often mesophilic bacteria that provide information about the prevailing community structure. Here we analyzed the metagenome profile based 16S rRNA amplicon sequencing of the three different springs from Deulajhari hot spring cluster, S1, S2 and S3, having a range of temperature (43°C to 65°C), pH (7.14 – 8.10) and variation in N, P, K, TOC, Salinity, COD and TDS. These thermal spring clusters are covered with the dense vegetation of Pandanus and continuously enriched by plant leaf debris, thus resulting in a high amount of total organic carbon (TOC). The number of phyla varied among the springs: 20 in S1 (43°C), 18 in S2 (55°C) and 24 in S3 (65°C) from the 16S rRNA data. Out of the reported phyla in each spring, the most abundant were Chloroflexi, Proteobacteria, Chlorobi and Acidobacteria, which correlated with the temperature gradient. Various metabolic pathways such as ABC transporters, Two-component system, Purine metabolism were most abundantly present in the S2 sample compared to the other two. The CCA analysis revealed the correlation between physiochemical parameters and their functional annotation. The present study establishes the relation between the physiological parameters and the structural distribution of microbiota along the temperature gradient.

The global rise in antibiotic resistance, fueled by indiscriminate antibiotic usage in medicine, aquaculture, agriculture, and the food industry, presents a significant public health challenge. Urban wastewater and sewage treatment plants have become key sources of antibiotic resistance proliferation. The present study focuses on the river Ganges in India, which is heavily impacted by human activities and serves as a potential hotspot for the spread of antibiotic resistance. We conducted a metagenomic analysis of sediment samples from six distinct locations along the river to assess the prevalence and diversity of antibiotic resistance genes (ARGs) within the microbial ecosystem. The metagenomic analysis revealed the predominance of Proteobacteria across regions of the river Ganges. The antimicrobial resistance (AMR) genes and virulence factors were determined by various databases. In addition to this, KEGG and COG analysis revealed important pathways related to AMR. The outcomes highlight noticeable regional differences in the prevalence of AMR genes. The findings suggest that enhancing health and sanitation infrastructure could play a crucial role in mitigating the global impact of AMR. This research contributes vital insights into the environmental aspects of antibiotic resistance, highlighting the importance of targeted public health interventions in the fight against AMR.

For the first time, we describe the whole genome of a yellow-pigmented, capsule-producing, pathogenic, and colistin-resistant Chryseobacterium gallinarum strain MGC42 isolated from a patient with urinary tract infection in India. VITEK 2 automated system initially identified this isolate as C. indologenes. However, 16S rRNA gene sequencing revealed that MGC42 shared 99.67% sequence identity with C. gallinarum–type strain DSM 27622. The draft genome of the strain MGC42 was 4,455,926 bp long with 37.08% Guanine-Cytosine (GC) content and was devoid of any plasmid. Antibiotic resistance, virulence, and toxin genes were predicted by implementing a machine learning classifier. Potential homologs of 340 virulence genes including hemolysin secretion protein D, metalloprotease, catalase peroxidases and autotransporter adhesins, type VI secretion system (T6SS) spike proteins, and 27 toxin factors including a novel toxin domain Ntox23 were identified in the genome. Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologs of 110 transporter proteins were predicted that were in agreement with moderate efflux activity. Twelve antibiotic resistance genes including two potentially novel putative β-lactamase genes sharing low similarity with known β-lactamase genes were also identified in the genome of this strain. The strain MGC42 was also resistant to several classes of antibiotics along with carbapenems and polymyxin. We also identified mutations in the orthologs of pmrB (M384T) and lpxD (I66V) that might be responsible for colistin resistance. The MGC42 strain shared 683 core genes with other environmental and clinical strains of Chryseobacterium species. Our findings suggest that the strain MGC42 is a multidrug-resistant, virulent pathogen and recommend 16S rRNA gene sequencing to identify clinical specimens of Chryseobacterium species.

Primary apical periodontitis occurs due to various insults to the dental pulp including microbial infections, physical and iatrogenic trauma, whereas inadequate elimination of intraradicular infection during root canal treatment may lead to secondary apical periodontitis. We explored the complex intra-radicular microbial communities and their functional potential through genome reconstruction. We applied shotgun metagenomic sequencing, binning and functional profiling to identify the significant contributors to infection at the acute and chronic apical periodontal lesions. Our analysis revealed the five classified clusters representing Enterobacter, Enterococcus, Lacticaseibacillus, Pseudomonas, Streptococcus and one unclassified cluster of contigs at the genus level. Of them, the major contributors were Pseudomonas, with 90.61% abundance in acute conditions, whereas Enterobacter followed by Enterococcus with 69.88% and 15.42% abundance, respectively, in chronic conditions. Enterobacter actively participated in antibiotic target alteration following multidrug efflux-mediated resistance mechanisms, predominant in the chronic stage. The prediction of pathways involved in the destruction of the supportive tissues of the tooth in Enterobacter and Pseudomonas support their crucial role in the manifestation of respective disease conditions. This study provides information about the differential composition of the microbiome in chronic and acute apical periodontitis. It takes a step to interpret the role of a single pathogen, solely or predominantly, in establishing endodontic infection types through genome reconstruction following high throughput metagenomic DNA analysis. The resistome prediction sheds a new light on the therapeutic treatment guidelines for endodontists. However, it needs further conclusive research to support this outcome using a larger number of samples with similar etiological conditions, but different demographic origin.