Direct metagenomics investigation of non-surgical hard-to-heal wounds: a review.

BACKGROUND: Non-surgical chronic wounds, including diabetes-related foot diseases (DRFD), pressure injuries (PIs) and venous leg ulcers (VLU), are common hard-to-heal wounds. Wound evolution partly depends on microbial colonisation or infection, which is often confused by clinicians, thereby hampering proper management. Current routine microbiology investigation of these wounds is based on in vitro culture, focusing only on a limited panel of the most frequently isolated bacteria, leaving a large part of the wound microbiome undocumented. METHODS: A literature search was conducted on original studies published through October 2022 reporting metagenomic next generation sequencing (mNGS) of chronic wound samples. Studies were eligible for inclusion if they applied 16 S rRNA metagenomics or shotgun metagenomics for microbiome analysis or diagnosis. Case reports, prospective, or retrospective studies were included. However, review articles, animal studies, in vitro model optimisation, benchmarking, treatment optimisation studies, and non-clinical studies were excluded. Articles were identified in PubMed, Google Scholar, Web of Science, Microsoft Academic, Crossref and Semantic Scholar databases. RESULTS: Of the 3,202 articles found in the initial search, 2,336 articles were removed after deduplication and 834 articles following title and abstract screening. A further 14 were removed after full text reading, with 18 articles finally included. Data were provided for 3,628 patients, including 1,535 DRFDs, 956 VLUs, and 791 PIs, with 164 microbial genera and 116 species identified using mNGS approaches. A high microbial diversity was observed depending on the geographical location and wound evolution. Clinically infected wounds were the most diverse, possibly due to a widespread colonisation by pathogenic bacteria from body and environmental microbiota. mNGS data identified the presence of virus (EBV) and fungi (Candida and Aspergillus species), as well as Staphylococcus and Pseudomonas bacteriophages. CONCLUSION: This study highlighted the benefit of mNGS for time-effective pathogen genome detection. Despite the majority of the included studies investigating only 16 S rDNA, ignoring a part of viral, fungal and parasite colonisation, mNGS detected a large number of bacteria through the included studies. Such technology could be implemented in routine microbiology for hard-to-heal wound microbiota investigation and post-treatment wound colonisation surveillance.

Cultivable epiphytic bacteria of the Chlorophyta Ulva sp.: diversity, antibacterial, and biofilm-modulating activities.

AIMS: Macroalgae harbor a rich epiphytic microbiota that plays a crucial role in algal morphogenesis and defense mechanisms. This study aims to isolate epiphytic cultivable microbiota from Ulva sp. surfaces. Various culture media were employed to evaluate a wide range of cultivable microbiota. Our objective was to assess the antibacterial and biofilm-modulating activities of supernatants from isolated bacteria. METHODS AND RESULTS: Sixty-nine bacterial isolates from Ulva sp. were identified based on 16S rRNA gene sequencing. Their antibacterial activity and biofilm modulation potential were screened against three target marine bacteria: 45%, mostly affiliated with Gammaproteobacteria and mainly grown on diluted R2A medium (R2Ad), showed strong antibacterial activity, while 18% had a significant impact on biofilm modulation. Molecular network analysis was carried out on four bioactive bacterial supernatants, revealing new molecules potentially responsible for their activities. CONCLUSION: R2Ad offered the greatest diversity and proportion of active isolates. The molecular network approach holds promise for both identifying bacterial isolates based on their molecular production and characterizing antibacterial and biofilm-modulating activities.

Diversity and Functionality of Bacteria Associated with Different Tissues of Spider Heteropoda venatoria Revealed through Integration of High-Throughput Sequencing and Culturomics Approaches.

Spiders host a diverse range of bacteria in their guts and other tissues, which have been found to play a significant role in their fitness. This study aimed to investigate the community diversity and functional characteristics of spider-associated bacteria in four tissues of Heteropoda venatoria using HTS of the 16S rRNA gene and culturomics technologies, as well as the functional verification of the isolated strains. The results of HTS showed that the spider-associated bacteria in different tissues belonged to 34 phyla, 72 classes, 170 orders, 277 families, and 458 genera. Bacillus was found to be the most abundant bacteria in the venom gland, silk gland, and ovary, while Stenotrophomonas, Acinetobacter, and Sphingomonas were dominant in the gut microbiota. Based on the amplicon sequencing results, 21 distinct cultivation conditions were developed using culturomics to isolate bacteria from the ovary, gut, venom gland, and silk gland. A total of 119 bacterial strains, representing 4 phyla and 25 genera, with Bacillus and Serratia as the dominant genera, were isolated. Five strains exhibited high efficiency in degrading pesticides in the in vitro experiments. Out of the 119 isolates, 28 exhibited antibacterial activity against at least one of the tested bacterial strains, including the pathogenic bacteria Staphylococcus aureus, Acinetobacter baumanii, and Enterococcus faecalis. The study also identified three strains, GL312, PL211, and PL316, which exhibited significant cytotoxicity against MGC-803. The crude extract from the fermentation broth of strain PL316 was found to effectively induce apoptosis in MGC-803 cells. Overall, this study offers a comprehensive understanding of the bacterial community structure associated with H. venatoria. It also provides valuable insights into discovering novel antitumor natural products for gastric cancer and xenobiotic-degrading bacteria of spiders.

Uncovering specific taxonomic and functional alteration of gut microbiota in chronic kidney disease through 16S rRNA data.

Introduction: Chronic kidney disease (CKD) is worldwide healthcare burden with growing incidence and death rate. Emerging evidence demonstrated the compositional and functional differences of gut microbiota in patients with CKD. As such, gut microbial features can be developed as diagnostic biomarkers and potential therapeutic target for CKD. Methods: To eliminate the outcome bias arising from factors such as geographical distribution, sequencing platform, and data analysis techniques, we conducted a comprehensive analysis of the microbial differences between patients with CKD and healthy individuals based on multiple samples worldwide. A total of 980 samples from six references across three nations were incorporated from the PubMed, Web of Science, and GMrepo databases. The obtained 16S rRNA microbiome data were subjected to DADA2 processing, QIIME2 and PICRUSt2 analyses. Results: The gut microbiota of patients with CKD differs significantly from that of healthy controls (HC), with a substantial decrease in the microbial diversity among the CKD group. Moreover, a significantly reduced abundance of bacteria Faecalibacterium prausnitzii (F. prausnitzii) was detected in the CKD group through linear discriminant analysis effect size (LEfSe) analysis, which may be associated with the alleviating effects against CKD. Notably, we identified CKD-depleted F. prausnitzii demonstrated a significant negative correlation with three pathways based on predictive functional analysis, suggesting its potential role in regulating systemic acidbase disturbance and pro-oxidant metabolism. Discussion: Our findings demonstrated notable alterations of gut microbiota in CKD patients. Specific gut-beneficial microbiota, especially F. prausnitzii, may be developed as a preventive and therapeutic tool for CKD clinical management.

Changing patterns of bacterial profile and antimicrobial resistance in high-risk patients during the COVID-19 pandemic at a tertiary oncology hospital.

The widespread evolution of phenotypic resistance in clinical isolates over the years, coupled with the COVID-19 pandemic onset, has exacerbated the global challenge of antimicrobial resistance. This study aimed to explore changes in bacterial infection patterns and antimicrobial resistance during the COVID-19 pandemic. This study involved the periods before and during COVID-19: the pre-pandemic and pandemic eras. The surveillance results of bacterial isolates causing infections in cancer patients at an Egyptian tertiary oncology hospital were retrieved. The Vitek®2 or Phoenix systems were utilized for species identification and susceptibility testing. Statistical analyses were performed comparing microbiological trends before and during the pandemic. Out of 2856 bacterial isolates, Gram-negative bacteria (GNB) predominated (69.7%), and Gram-positive bacteria (GPB) comprised 30.3% of isolates. No significant change was found in GNB prevalence during the pandemic (P = 0.159). Elevated rates of Klebsiella and Pseudomonas species were demonstrated during the pandemic, as was a decrease in E. coli and Acinetobacter species (P < 0.001, 0.018, < 0.001, and 0.046, respectively) in hematological patients. In surgical patients, Enterobacteriaceae significantly increased (P = 0.012), while non-fermenters significantly decreased (P = 0.007). GPB species from either hematological or surgical wards exhibited no notable changes during the pandemic. GNB resistance increased in hematological patients to carbapenems, amikacin, and tigecycline and decreased in surgical patients to amikacin and cefoxitin (P < 0.001, 0.010, < 0.001, < 0.001, and 0.016, respectively). The study highlights notable shifts in the microbial landscape during the COVID-19 pandemic, particularly in the prevalence and resistance patterns of GNB in hematological and surgical wards.

Establishment of a Multiplex Detection Method for Common Bacteria in Blood Based on Human Mannan-Binding Lectin Protein-Conjugated Magnetic Bead Enrichment Combined with Recombinase-Aided PCR Technology.

Objective: Recombinase-aided polymerase chain reaction (RAP) is a sensitive, single-tube, two-stage nucleic acid amplification method. This study aimed to develop an assay that can be used for the early diagnosis of three types of bacteremia caused by Staphylococcus aureus (SA), Pseudomonas aeruginosa (PA), and Acinetobacter baumannii (AB) in the bloodstream based on recombinant human mannan-binding lectin protein (M1 protein)-conjugated magnetic bead (M1 bead) enrichment of pathogens combined with RAP. Methods: Recombinant plasmids were used to evaluate the assay sensitivity. Common blood influenza bacteria were used for the specific detection. Simulated and clinical plasma samples were enriched with M1 beads and then subjected to multiple recombinase-aided PCR (M-RAP) and quantitative PCR (qPCR) assays. Kappa analysis was used to evaluate the consistency between the two assays. Results: The M-RAP method had sensitivity rates of 1, 10, and 1 copies/µL for the detection of SA, PA, and AB plasmids, respectively, without cross-reaction to other bacterial species. The M-RAP assay obtained results for < 10 CFU/mL pathogens in the blood within 4 h, with higher sensitivity than qPCR. M-RAP and qPCR for SA, PA, and AB yielded Kappa values of 0.839, 0.815, and 0.856, respectively ( P < 0.05). Conclusion: An M-RAP assay for SA, PA, and AB in blood samples utilizing M1 bead enrichment has been developed and can be potentially used for the early detection of bacteremia.

Gut microbiome and metabolome to discover pathogenic bacteria and probiotics in ankylosing spondylitis.

Objective: Previous research has partially revealed distinct gut microbiota in ankylosing spondylitis (AS). In this study, we performed non-targeted fecal metabolomics in AS in order to discover the microbiome-metabolome interface in AS. Based on prospective cohort studies, we further explored the impact of the tumor necrosis factor inhibitor (TNFi) on the gut microbiota and metabolites in AS. Methods: To further understand the gut microbiota and metabolites in AS, along with the influence of TNFi, we initiated a prospective cohort study. Fecal samples were collected from 29 patients with AS before and after TNFi therapy and 31 healthy controls. Metagenomic and metabolomic experiments were performed on the fecal samples; moreover, validation experiments were conducted based on the association between the microbiota and metabolites. Results: A total of 7,703 species were annotated using the metagenomic sequencing system and by profiling the microbial community taxonomic composition, while 50,046 metabolites were identified using metabolite profiling. Differential microbials and metabolites were discovered between patients with AS and healthy controls. Moreover, TNFi was confirmed to partially restore the gut microbiota and the metabolites. Multi-omics analysis of the microbiota and metabolites was performed to determine the associations between the differential microbes and metabolites, identifying compounds such as oxypurinol and biotin, which were correlated with the inhibition of the pathogenic bacteria Ruminococcus gnavus and the promotion of the probiotic bacteria Bacteroides uniformis. Through experimental studies, the relationship between microbes and metabolites was further confirmed, and the impact of these two types of microbes on the enterocytes and the inflammatory cytokine interleukin-18 (IL-18) was explored. Conclusion: In summary, multi-omics exploration elucidated the impact of TNFi on the gut microbiota and metabolites and proposed a novel therapeutic perspective: supplementation of compounds to inhibit potential pathogenic bacteria and to promote potential probiotics, therefore controlling inflammation in AS.

A fluorescent sensor array based on antibiotic-stabilized metal nanoclusters for the multiplex detection of bacteria.

To address the need for facile, rapid detection of pathogens in water supplies, a fluorescent sensing array platform based on antibiotic-stabilized metal nanoclusters was developed for the multiplex detection of pathogens. Using five common antibiotics, eight different nanoclusters (NCs) were synthesized including ampicillin stabilized copper NCs, cefepime stabilized gold and copper NCs, kanamycin stabilized gold and copper NCs, lysozyme stabilized gold NCs, and vancomycin stabilized gold/silver and copper NCs. Based on the different interaction of each NC with the bacteria strains, unique patterns were generated. Various machine learning algorithms were employed for pattern discernment, among which the artificial neural networks proved to have the highest performance, with an accuracy of 100%. The developed prediction model performed well on an independent test dataset and on real samples gathered from drinking water, tap water and the Anzali Lagoon water, with prediction accuracy of 96.88% and 95.14%, respectively. This work demonstrates how generic antibiotics can be implemented for NC synthesis and used as recognition elements for pathogen detection. Furthermore, it displays how merging machine learning techniques can elevate sensitivity of analytical devices.

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.

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.

Application value of metagenomic next-generation sequencing in hematological patients with high-risk febrile neutropenia.

Background: Metagenomic next-generation sequencing (mNGS) is a novel non-invasive and comprehensive technique for etiological diagnosis of infectious diseases. However, its practical significance has been seldom reported in the context of hematological patients with high-risk febrile neutropenia, a unique patient group characterized by neutropenia and compromised immune responses. Methods: This retrospective study evaluated the results of plasma cfDNA sequencing in 164 hematological patients with high-risk febrile neutropenia. We assessed the diagnostic efficacy and clinical impact of mNGS, comparing it with conventional microbiological tests. Results: mNGS identified 68 different pathogens in 111 patients, whereas conventional methods detected only 17 pathogen types in 36 patients. mNGS exhibited a significantly higher positive detection rate than conventional methods (67.7% vs. 22.0%, P < 0.001). This improvement was consistent across bacterial (30.5% vs. 9.1%), fungal (19.5% vs. 4.3%), and viral (37.2% vs. 9.1%) infections (P < 0.001 for all comparisons). The anti-infective treatment strategies were adjusted for 51.2% (84/164) of the patients based on the mNGS results. Conclusions: mNGS of plasma cfDNA offers substantial promise for the early detection of pathogens and the timely optimization of anti-infective therapies in hematological patients with high-risk febrile neutropenia.

Gut Microbiota Profiles in Myopes and Nonmyopes.

Purpose: To identify compositional differences in the gut microbiome of nonmyopes (NM) and myopes using 16S ribosomal RNA sequencing and to investigate whether the microbiome may contribute to the onset or progression of the condition. Methods: Faecal samples were collected from 52 adult participants, of whom 23 were NM, 8 were progressive myopes (PM), and 21 were stable myopes (SM). The composition of the gut microbiota in each group was analysed using 16S ribosomal RNA gene sequencing. Results: There were no significant differences in alpha and beta diversity between the three groups (NM, PM, and SM). However, the distributions of Bifidobacterium, Bacteroides, Megamonas, Faecalibacterium, Coprococcus, Dorea, Roseburia, and Blautia were significantly higher in the myopes (SM and PM combined) when compared with emmetropes. The myopes exhibited significantly greater abundance of bacteria that are linked to the regulation of dopaminergic signalling, such as Clostridium, Ruminococcus, Bifidobacterium, and Bacteroides. Individuals with stable myopia were found to have a significantly higher proportion of Prevotella copri than those with progressive myopia. Bifidobacterium adolescentis, a gamma-aminobutyric acid (GABA)-producing bacterium, was significantly higher in all myopes than in NM and, in the comparison between SM and PM, it is significantly higher in SM. B. uniformis and B. fragilis, both GABA-producing Bacteroides, were present in relatively high abundance in all myopes and in SM compared with PM, respectively. Conclusions: The presence of bacteria related to dopamine effect and GABA-producing bacteria in the gut microbiome of myopes may suggest a role of these microorganisms in the onset and progression of myopia.

A comparison between full-length 16S rRNA Oxford nanopore sequencing and Illumina V3-V4 16S rRNA sequencing in head and neck cancer tissues.

Describing the microbial community within the tumour has been a key aspect in understanding the pathophysiology of the tumour microenvironment. In head and neck cancer (HNC), most studies on tissue samples have only performed 16S rRNA short-read sequencing (SRS) on V3-V5 region. SRS is mostly limited to genus level identification. In this study, we compared full-length 16S rRNA long-read sequencing (FL-ONT) from Oxford Nanopore Technology (ONT) to V3-V4 Illumina SRS (V3V4-Illumina) in 26 HNC tumour tissues. Further validation was also performed using culture-based methods in 16 bacterial isolates obtained from 4 patients using MALDI-TOF MS. We observed similar alpha diversity indexes between FL-ONT and V3V4-Illumina. However, beta-diversity was significantly different between techniques (PERMANOVA - R2 = 0.131, p < 0.0001). At higher taxonomic levels (Phylum to Family), all metrics were more similar among sequencing techniques, while lower taxonomy displayed more discrepancies. At higher taxonomic levels, correlation in relative abundance from FL-ONT and V3V4-Illumina were higher, while this correlation decreased at lower levels. Finally, FL-ONT was able to identify more isolates at the species level that were identified using MALDI-TOF MS (75% vs. 18.8%). FL-ONT was able to identify lower taxonomic levels at a better resolution as compared to V3V4-Illumina 16S rRNA sequencing.

Dental plaque microbiota sequence counts for microbial profiling and resistance genes detection.

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.

Oral microbiome dysbiosis among cigarette smokers and smokeless tobacco users compared to non-users.

Tobacco use significantly influences the oral microbiome. However, less is known about how different tobacco products specifically impact the oral microbiome over time. To address this knowledge gap, we characterized the oral microbiome of cigarette users, smokeless tobacco users, and non-users over 4 months (four time points). Buccal swab and saliva samples (n = 611) were collected from 85 participants. DNA was extracted from all samples and sequencing was carried out on an Illumina MiSeq, targeting the V3-V4 region of the 16S rRNA gene. Cigarette and smokeless tobacco users had more diverse oral bacterial communities, including a higher relative abundance of Firmicutes and a lower relative abundance of Proteobacteria, when compared to non-users. Non-users had a higher relative abundance of Actinomyces, Granulicatella, Haemophilus, Neisseria, Oribacterium, Prevotella, Pseudomonas, Rothia, and Veillonella in buccal swab samples, compared to tobacco users. While the most abundant bacterial genera were relatively constant over time, some species demonstrated significant shifts in relative abundance between the first and last time points. In addition, some opportunistic pathogens were detected among tobacco users including Neisseria subflava, Bulleidia moorei and Porphyromonas endodontalis. Overall, our results provide a more holistic understanding of the structure of oral bacterial communities in tobacco users compared to non-users.

Comparative characterization of supragingival plaque microbiomes in malocclusion adult female patients undergoing orthodontic treatment with removable aligners or fixed appliances: a descriptive cross-sectional study.

Objectives: This study aimed to explore the effects of removable aligners and fixed appliances on the supragingival bacterial communities in adult female patients undergoing orthodontic treatment. Methods: Supragingival plaque samples from 48 female individuals underwent microbiome analysis (16S rRNA gene sequencing) using PacBio Sequel sequencing. The study included 13 adults without orthodontic treatment needs as the control group (Group C), and 35 patients with comparable initial orthodontic conditions who received treatment at a university clinic in Beijing, China. The treatment involved either traditional fixed brackets (Group B, n = 17) or Invisalign® aligners (Group AT, n = 18). Bioinformatics methods were used for data analysis. Results: From the 48 plaque samples, a total of 334,961 valid reads were obtained, averaging 6,978 sequences per sample. The 16S rDNA sequences were classified into 25,727 amplicon sequence variants (ASVs). Significant variances in alpha and beta diversity among the groups were noted. Group B microbiome exhibited an increased presence of Gram-negative bacteria. At the phylum level, Actinobacteriota was significantly more prevalent in Group C samples, while Bacteroidota was enriched in Group B samples. Family-level relative abundance analysis showed a notable increase in Saccharibacteria (formerly TM7) and Prevotellaceae in Group B. Genus-level analysis revealed a significant rise in Lautropia in Group AT. Fixed orthodontic appliances were linked to oral microbiome changes, notably an enhanced relative abundance of anaerobes, including periodontal pathogens. Conclusion: The observation points to the impact of orthodontic appliance on the oral microbial community, highlighting the difference between traditional braces (Group B) and clear aligners (Group AT)in terms of the predominance of anaerobic and gram negative bacteria. This emphasizes the importance of considering the microbiological effects when choosing orthodontic appliance and underscores the need for tailored oral hygiene practices for individuals undergoing these treatments. This research might provide insights that could assist in the development of innovative cleaning techniques and antibacterial materials.

Description of a 'plankton filtration bias' in sequencing-based bacterial community analysis and of an Arduino microcontroller-based flowmeter device that can help to resolve it.

Diversity studies of aquatic picoplankton (bacterioplankton) communities using size-class filtration, DNA extraction, PCR and sequencing of phylogenetic markers, require a robust methodological pipeline, since biases have been demonstrated essentially at all levels, including DNA extraction, primer choice and PCR. Even different filtration volumes of the same plankton sample and, thus, different biomass loading of the filters, can distort the sequencing results. In this study, we designed an Arduino microcontroller-based flowmeter that records the decrease of initial (maximal) flowrate as proxy for increasing biomass loading and clogging of filters during plankton filtration. The device was tested using freshwater plankton of Lake Constance, and total DNA was extracted and an 16S rDNA amplicon was sequenced. We confirmed that different filtration volumes used for the same water sample affect the sequencing results. Differences were visible in alpha and beta diversities and across all taxonomic ranks. Taxa most affected were typical freshwater Actinobacteria and Bacteroidetes, increasing up to 38% and decreasing up to 29% in relative abundance, respectively. In another experiment, a lake water sample was filtered undiluted and three-fold diluted, and each filtration was stopped once the flowrate had reduced to 50% of initial flowrate, hence, at the same degree of filter clogging. The three-fold diluted sample required three-fold filtration volumes, while equivalent amounts of total DNA were extracted and differences across all taxonomic ranks were not statistically significant compared to the undiluted controls. In conclusion, this work confirms a volume/biomass-dependent bacterioplankton filtration bias for sequencing-based community analyses and provides an improved procedure for controlling biomass loading during filtrations and recovery of equivalent amounts of DNA from samples independent of the plankton density. The application of the device can also avoid the distorting of sequencing results as caused by the plankton filtration bias.