SARS-CoV-2, a severe respiratory disease primarily targeting the lungs, was the leading cause of death worldwide during the pandemic. Understanding the interplay between the oral microbiome and inflammatory cytokines during acute infection is crucial for elucidating host immune responses. This study aimed to explore the relationship between the oral microbiome and cytokines in COVID-19 patients, particularly those with and without sputum production. Saliva and blood samples from 50 COVID-19 patients were subjected to 16S ribosomal RNA gene sequencing for oral microbiome analysis, and 65 saliva and serum cytokines were assessed using Luminex multiplex analysis. The Mann-Whitney test was used to compare cytokine levels between individuals with and without sputum production. Logistic regression machine learning models were employed to evaluate the predictive capability of oral microbiome, salivary, and blood biomarkers for sputum production. Significant differences were observed in the membership (Jaccard dissimilarity: p = 0.016) and abundance (PhILR dissimilarity: p = 0.048; metagenomeSeq) of salivary microbial communities between patients with and without sputum production. Seven bacterial genera, including Prevotella, Streptococcus, Actinomyces, Atopobium, Filifactor, Leptotrichia, and Selenomonas, were more prevalent in patients with sputum production (p<0.05, Fisher\'s exact test). Nine genera, including Prevotella, Megasphaera, Stomatobaculum, Selenomonas, Leptotrichia, Veillonella, Actinomyces, Atopobium, and Corynebacteria, were significantly more abundant in the sputum-producing group, while Lachnoanaerobaculum was more prevalent in the non-sputum-producing group (p<0.05, ANCOM-BC). Positive correlations were found between salivary IFN-gamma and Eotaxin2/CCL24 with sputum production, while negative correlations were noted with serum MCP3/CCL7, MIG/CXCL9, IL1 beta, and SCF (p<0.05, Mann-Whitney test). The machine learning model using only oral bacteria input outperformed the model that included all data: blood and saliva biomarkers, as well as clinical and demographic variables, in predicting sputum production in COVID-19 subjects. The performance metrics were as follows, comparing the model with only bacteria input versus the model with all input variables: precision (95% vs. 75%), recall (100% vs. 50%), F1-score (98% vs. 60%), and accuracy (82% vs. 66%).

This study aimed to identify the oral microbiota factors contributing to low birth weight (LBW) in Chinese pregnant women and develop a prediction model using machine learning.
A nested case-control study was conducted in a prospective cohort of 580 Chinese pregnant women, with 23 LBW cases and 23 healthy delivery controls matched for age and smoking habit. Saliva samples were collected at early and late pregnancy, and microbiome profiles were analyzed through 16S rRNA gene sequencing.
The relative abundance of Streptococcus was over-represented (median 0.259 vs. 0.116) and Saccharibacteria_TM7 was under-represented (median 0.033 vs. 0.068) in the LBW case group than in controls (p < 0.001, p = 0.015 respectively). Ten species were identified as microbiome biomarkers of LBW by LEfSe analysis, which included 7 species within the genus of Streptococcus or as part of \'nutritionally variant streptococci\' (NVS), 2 species of opportunistic pathogen Leptotrichia buccalis and Gemella sanguinis (all LDA score>3.5) as risk biomarkers, and one species of Saccharibacteria TM7 as a beneficial biomarker (LDA= -4.5). The machine-learning model based on these 10 distinguished oral microbiota species could predict LBW, with an accuracy of 82 %, sensitivity of 91 %, and specificity of 73 % (AUC-ROC score 0.89, 95 % CI: 0.75-1.0). Results of α-diversity showed that mothers who delivered LBW infants had less stable salivary microbiota construction throughout pregnancy than the control group (measured by Shannon, p = 0.048; and Pielou\'s, p = 0.021), however the microbiome diversity did not improve the prediction accuracy of LBW.
A machine-learning oral microbiome model shows promise in predicting low-birth-weight delivery. Even in cases where oral health is not significantly compromised, opportunistic pathogens or rarer taxa associated with adverse pregnancy outcomes can still be identified in the oral cavity.
This study highlights the potential complexity of the relationship between oral microbiome and pregnancy outcomes, indicating that mechanisms underlying the association between oral microbiota and adverse pregnancy outcomes may involve complex interactions between host factors, microbiota, and systemic conditions. Using machine learning to develop a predictive model based on specific oral microbiota biomarkers provides a potential for personalized medicine approaches. Future prediction models should incorporate clinical metadata to be clinically useful for improving maternal and child health.

Type VI CRISPR-Cas systems are among the few CRISPR varieties that target exclusively RNA. The CRISPR RNA-guided, sequence-specific binding of target RNAs, such as phage transcripts, activates the type VI effector, Cas13. Once activated, Cas13 causes collateral RNA cleavage, which induces bacterial cell dormancy, thus protecting the host population from the phage spread. We show here that the principal form of collateral RNA degradation elicited by Leptotrichia shahii Cas13a expressed in Escherichia coli cells is the cleavage of anticodons in a subset of transfer RNAs (tRNAs) with uridine-rich anticodons. This tRNA cleavage is accompanied by inhibition of protein synthesis, thus providing defense from the phages. In addition, Cas13a-mediated tRNA cleavage indirectly activates the RNases of bacterial toxin-antitoxin modules cleaving messenger RNA, which could provide a backup defense. The mechanism of Cas13a-induced antiphage defense resembles that of bacterial anticodon nucleases, which is compatible with the hypothesis that type VI effectors evolved from an abortive infection module encompassing an anticodon nuclease.

BACKGROUND: The aim of the present study was to evaluate the subgingival microbiome in patients with grade C molar-incisor pattern periodontitis (C-MIP) affecting the primary or permanent dentitions.
METHODS: DNA was isolated from subgingival biofilm samples from diseased and healthy sites from 45 C-MIP patients and subjected to phylogenetic microarray analysis. C-MIP sites were compared between children affected in the primary to those affected in the permanent dentitions. Within-subject differences between C-MIP-affected sites and dentition-matched healthy sites were also evaluated.
RESULTS: C-MIP sites of subjects affected in the primary dentition showed partially overlapping but distinct microbial communities from C-MIP permanent dentition sites (p < 0.05). Differences were due to increased levels in primary C-MIP sites of certain species of the genera Capnocytophaga and Leptotrichia, while C-MIP permanent dentition sites showed higher prevalence of Filifactor alocis. Aggregatibacter actinomycetemcomitans (Aa) was among species seen in high prevalence and levels in both primary and permanent C-MIP sites. Moreover, both permanent and primary C-MIP sites showed distinct microbial communities when compared to dentition-matched healthy sites in the same subject (p < 0.01).
CONCLUSIONS: Primary and permanent teeth with C-MIP showed a dysbiotic microbiome, with children affected in the primary dentition showing a distinct profile from those affected in the permanent dentition. However, Aa was enriched in both primary and permanent diseased sites, confirming that this microorganism is implicated in C-MIP in both dentitions.

The tumor microbiome, a relatively new research field, affects tumor progression through several mechanisms. The Cancer Microbiome Atlas (TCMA) database was recently published. In the present study, we used TCMA and The Cancer Genome Atlas and examined microbiome profiling in head and neck squamous cell carcinoma (HNSCC), the role of the intratumoral microbiota in the prognosis of HNSCC patients, and differentially expressed genes in tumor cells in relation to specific bacterial infections. We investigated 18 microbes at the genus level that differed between solid normal tissue (n = 22) and primary tumors (n = 154). The tissue microbiome profiles of Actinomyces, Fusobacterium, and Rothia at the genus level differed between the solid normal tissue and primary tumors of HNSCC patients. When the prognosis of groups with rates over and under the median for each microbe at the genus level was examined, rates for Leptotrichia which were over the median correlated with significantly higher overall survival rates. We then extracted 35 differentially expressed genes between the over- and under-the-median-for-Leptotrichia groups based on the criteria of >1.5 fold and p < 0.05 in the Mann-Whitney U-test. A pathway analysis showed that these Leptotrichia-related genes were associated with the pathways of Alzheimer disease, neurodegeneration-multiple diseases, prion disease, MAPK signaling, and PI3K-Akt signaling, while protein-protein interaction analysis revealed that these genes formed a dense network. In conclusion, probiotics and specific antimicrobial therapy targeting Leptotrichia may have an impact on the prognosis of HNSCC.

BACKGROUND: Leptotrichia spp. are fastidious facultative anaerobic, pencil-shaped, gramnegative rods that reside in the mouths, intestines, and female genital tracts of humans. Bacteremia and septic shock have been rarely reported in the immunocompromised host. We report a case of L. trevisanii bacteremia in a patient recently diagnosed with acute myeloid leukemia (AML) on chemotherapy.
METHODS: A 75-year-old male with a history of diabetes, chronic kidney disease, and coronary artery disease status post-CABG presented with neutropenic fevers and signs of sepsis after the initiation of chemotherapy. Blood cultures were ordered and extensive gene sequencing helped identify Leptotrichia trevisanii as the causative pathogen. Subsequently, the patient was successfully treated with empiric cefepime.
CONCLUSIONS: Opportunistic pathogens are involved in a variety of diseases and have been isolated from immunocompromised patients undergoing transplantation or in patients with comorbidities, like leukemia, lymphoma, or neutropenia. L. trevisanii has been reported as a cause of bloodstream infections in patients with hematologic malignancies receiving chemotherapy.
CONCLUSIONS: This case highlights the key role that Leptotrichia trevisanii plays in the introduction of sepsis among immunocompromised patients, particularly with hematologic malignancies, like AML, on chemotherapy.

Antibiotics play an important role in treating periodontal diseases. Due to the effectiveness of antibiotic therapies, their usage in dentistry has significantly increased. The aim of this study focused on the in-vitro susceptibility of different gram-negative oral bacteria species - which are associated with periodontal diseases (Fusobacterium spp., Capnocytophaga spp. and Leptotrichia buccalis) and have different geographical origins (Asia and Europe) - against antimicrobials that are clinically relevant in dental therapy.
A total of 45 strains were tested (29 Fusobacterium spp., 13 Capnocytophaga spp. and 3 L. buccalis) that were either isolated from Chinese patients or were obtained from different strain collections. Their antimicrobial susceptibility to the antimicrobial agents benzylpenicillin, amoxicillin, amoxicillin-clavulanic acid, ciprofloxacin, moxifloxacin, clindamycin, doxycycline, tetracycline and metronidazole was tested using the E-Test. Strains with particular resistance to penicillin, clindamycin and metronidazole were further analysed for resistance genes.
All tested bacterial isolates were sensitive to amoxicillin, amoxicillin-clavulanic acid, doxycycline and tetracycline, but showed variable sensitivity towards other antibiotics such as benzylpenicillin, ciprofloxacin, moxifloxacin, clindamycin and metronidazole.
The results of the present study suggest that certain periodontal disease-related bacterial strains can be resistant towards antimicrobial agents commonly used in adjuvant periodontal therapy.

The oral microbiome is an emerging field that has been a topic of discussion since the development of next generation sequencing and the implementation of the human microbiome project. This article reviews the current literature surrounding the oral microbiome, briefly highlighting most recent methods of microbiome characterization including cutting edge omics, databases for the microbiome, and areas with current gaps in knowledge. This article also describes reports on microorganisms contained in the oral microbiome which include viruses, archaea, fungi, and bacteria, and provides an in-depth analysis of their significant roles in tissue homeostasis. Finally, we detail key bacteria involved in oral disease, including oral cancer, and the current research surrounding their role in stimulation of inflammatory cytokines, the role of gingival crevicular fluid in periodontal disease, the creation of a network of interactions between microorganisms, the influence of the planktonic microbiome and cospecies biofilms, and the implications of antibiotic resistance. This paper provides a comprehensive literature analysis while also identifying gaps in knowledge to enable future studies to be conducted.

Leptotrichia species are anaerobic, Gram-negative bacilli increasingly recognized as pathogens capable of causing invasive infections such as bloodstream infection (BSI), particularly among immunocompromised patients. However, there is a paucity of data regarding epidemiology, antimicrobial susceptibility, optimal treatment, and clinical outcomes among patients with Leptotrichia bacteremia. Patient risk factors, treatment approaches, and outcomes of a retrospective cohort of adult patients with Leptotrichia BSI at a tertiary medical center (Mayo Clinic Rochester [MCR]) were evaluated. Concurrently, species, temporal trends, and antimicrobial susceptibility testing (AST) results of Leptotrichia isolates submitted to a reference laboratory (Mayo Clinic Laboratories) over the past 10 years were examined. We identified 224 blood culture isolates of Leptotrichia species, with 26 isolates from patients treated at MCR. The most frequent species included L. trevisanii (49%), L. buccalis (24%), and L. wadei (16%). Leptotrichia species demonstrated >90% susceptibility to penicillin, metronidazole, ertapenem, and piperacillin-tazobactam. However, 96% (74/77) of isolates were resistant to moxifloxacin. For patients treated at MCR, the mean patient age was 55 years (standard deviation [SD], 17), with 9 females (35%), and all were neutropenic at the time of BSI. The primary sources of infection were gastrointestinal (58%), intravascular catheter (35%), and odontogenic (15%). Patients were treated with metronidazole (42%), piperacillin-tazobactam (27%), or carbapenems (19%). The mean duration of treatment was 11 days (SD, 4.5), with a 60-day all-cause mortality of 19% and no microbiologic relapse. Leptotrichia species are rare but important causes of BSI in neutropenic patients. Due to evolving antimicrobial susceptibility profiles, a review of AST results is necessary when selecting optimal antimicrobial therapy.

Coevolution of microbiome and immunity at mucosal sites is essential for our health. Whether the oral microbiome, the second largest community after the gut, contributes to the immunogenicity of COVID-19 vaccines is not known. We investigated the baseline oral microbiome in individuals in the COVAXID clinical trial receiving the BNT162b2 mRNA vaccine. Participants (n=115) included healthy controls (HC; n=57) and people living with HIV (PLHIV; n=58) who met the study selection criteria. Vaccine-induced Spike antibodies in saliva and serum from 0 to 6 months were assessed and comparative analyses were performed against the individual salivary 16S ASV microbiome diversity. High- versus low vaccine responders were assessed on general, immunological, and oral microbiome features. Our analyses identified oral microbiome features enriched in high- vs. low-responders among healthy and PLHIV participants. In low-responders, an enrichment of Gram-negative, anaerobic species with proteolytic activity were found including Campylobacter, Butyrivibrio, Selenomonas, Lachnoanaerobaculum, Leptotrichia, Megasphaera, Prevotella and Stomatobaculum. In high-responders, enriched species were mainly Gram-positive and saccharolytic facultative anaerobes: Abiotrophia, Corynebacterium, Gemella, Granulicatella, Rothia, and Haemophilus. Combining identified microbial features in a classifier using the area under the receiver operating characteristic curve (ROC AUC) yielded scores of 0.879 (healthy controls) to 0.82 (PLHIV), supporting the oral microbiome contribution in the long-term vaccination outcome. The present study is the first to suggest that the oral microbiome has an impact on the durability of mucosal immunity after Covid-19 vaccination. Microbiome-targeted interventions to enhance long-term duration of mucosal vaccine immunity may be exploited.