Leptotrichia Buccalis: A Novel Cause of Chorioamnionitis

Can oral microbiome predict low birth weight infant delivery?

OBJECTIVES

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

CLINICAL SIGNIFICANCE

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.

Subgingival Microbiome in Pregnancy and a Potential Relationship to Early Term Birth

Background

Periodontal disease in pregnancy is considered a risk factor for adverse birth outcomes. Periodontal disease has a microbial etiology, however, the current state of knowledge about the subgingival microbiome in pregnancy is not well understood.

Objective

To characterize the structure and diversity of the subgingival microbiome in early and late pregnancy and explore relationships between the subgingival microbiome and preterm birth among pregnant Black women.

Methods

This longitudinal descriptive study used 16S rRNA sequencing to profile the subgingival microbiome of 59 Black women and describe microbial ecology using alpha and beta diversity metrics. We also compared microbiome features across early (8-14 weeks) and late (24-30 weeks) gestation overall and according to gestational age at birth outcomes (spontaneous preterm, spontaneous early term, full term).

Results

In this sample of Black pregnant women, the top twenty bacterial taxa represented in the subgingival microbiome included a spectrum representative of various stages of biofilm progression leading to periodontal disease, including known periopathogens Porphyromonas gingivalis and Tannerella forsythia. Other organisms associated with periodontal disease reflected in the subgingival microbiome included several Prevotella spp., and Campylobacter spp. Measures of alpha or beta diversity did not distinguish the subgingival microbiome of women according to early/late gestation or full term/spontaneous preterm birth; however, alpha diversity differences in late pregnancy between women who spontaneously delivered early term and women who delivered full term were identified. Several taxa were also identified as being differentially abundant according to early/late gestation, and full term/spontaneous early term births.

Conclusions

Although the composition of the subgingival microbiome is shifted toward complexes associated with periodontal disease, the diversity of the microbiome remains stable throughout pregnancy. Several taxa were identified as being associated with spontaneous early term birth. Two, in particular, are promising targets of further investigation. Depletion of the oral commensal Lautropia mirabilis in early pregnancy and elevated levels of Prevotella melaninogenica in late pregnancy were both associated with spontaneous early term birth.

Highly multiplexed spatial mapping of microbial communities

Mapping the complex biogeography of microbial communities in situ with high taxonomic and spatial resolution poses a major challenge because of the high density¹ and rich diversity² of species in environmental microbiomes and the limitations of optical imaging technology^3–6. Here, we introduce High Phylogenetic Resolution microbiome mapping by Fluorescence in situ Hybridization (HiPR-FISH), a versatile technology that uses binary encoding, spectral imaging, and machine learning based decoding to create micron-scale maps of the locations and identities of hundreds of microbial species in complex communities. We demonstrate the ability of 10-bit HiPR-FISH to distinguish 1023 E. coli isolates, each fluorescently labeled with a unique binary barcode. HiPR-FISH, in conjunction with custom algorithms for automated probe design and single-cell image analysis, reveals the disruption of spatial networks in the mouse gut microbiome in response to antibiotic treatment and the longitudinal stability of spatial architectures in the human oral plaque microbiome. Combined with super-resolution imaging, HiPR-FISH reveals the diverse ribosome organization strategies of human oral microbial taxa. HiPR-FISH provides a framework for analyzing the spatial ecology of environmental microbial communities at single-cell resolution.

Oceanivirga miroungae sp. nov., isolated from oral cavity of northern elephant seal (Mirounga angustirostris)

Two independent strains of a Leptotrichia species (ES3154-GLU^T and ES2714_GLU) were isolated from the oral cavity of northern elephant seals (Mirounga angustirostris) that were admitted to The Marine Mammal Centre facilities in California, USA. The strains were isolated from oral swabs by cultivation in PPLO broth supplemented with serum, penicillin and colistin in anaerobic conditions. The strains were Gram-negative, pleomorphic, indole-, oxidase- and catalase-negative, non-spore-forming, non-motile rods/coccobacilli in short chains. The 16S rRNA gene sequence of these strains shared 94.42 % nucleotide similarity with Oceanivirga salmonicida AVG 2115^T but demonstrated ≤86.00-92.50 % nucleotide similarity to the 16S rRNA genes of other species of the family Leptotrichiaceae. The genome was sequenced for strain ES3154-GLU^T. Average nucleotide identity values between strain ES3154-GLU^T and 15 type strain genomes from the family Leptotrichiaceae ranged from 66.74 % vs. Sebaldella termitidis to 73.35 % vs. O. salmonicida. The whole genome phylogeny revealed that the novel species was most closely related to O. salmonicida AVG 2115^T. This relationship was also confirmed by nucleotide similarity and multilocus phylogenetic analyses employing various housekeeping genes (partial 23S rRNA, rpoB, rpoC, rpoD, polC, adh, gyrA and gyrB genes). Chemotaxonomic and phenotypical features of strain ES3154-GLU^T were in congruence with closely related members of the family Leptotrichiaceae, represented by similar enzyme profiles and fatty acid patterns. MALDI-TOF MS analysis was capable to clearly discriminate strain ES3154-GLU^T from all currently described taxa of the family Leptotrichiaceae. Based on these data, we propose a novel species of the genus Oceanivirga, for which the name Oceanivirga miroungae sp. nov. is proposed with the type strain ES3154-GLU^T (=DSM 109740^T=CCUG 73653^T=ATCC TSD-189^T=NCTC 14411^T) and one representative strain ES2714_GLU. The G+C content is 26.82 %, genome size is 1 356 983 bp.

Cárdenas KC, Barberis C, Ramirez MS, Famiglietti A, Vay C. Performance of MALDI-TOF Mass Spectrometry for the Identification of the HACEK Group and Other Fastidious Gram-Negative Rods

Objective:

The aim of this study was to determine the capacity of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) to identify 155 HACEK clinical isolates and other fastidious or infrequently isolated Gram-negative rods (e.g., Actinobacillus, Capnocytophaga, Pasteurella, Neisseria, Moraxella, Dysgonomonas, among others).

Methods:

All the isolates were identified by standard biochemical tests and MALDI-TOF MS. Two different extraction methods (direct transfer formic acid method on spot and ethanol formic acid extraction method) and different cut-offs for genus/specie level identification were used. MALDI-TOF MS identification was considered correct when the result obtained from the MS database agreed with the phenotypic identification result. When both the methods gave discordant results, the 16S rDNA gene sequencing was considered as the gold standard identification method.

Results:

Employing the score cut-offs suggested by the manufacturer, 93.55% and 69.03% isolates were correctly identified at the genus and species level, respectively. On the contrary , employing lower cut-off scores for identification, 98.06% and 92.09% isolates were properly identified at the genus and species level respectively and no significant differences between the results obtained with two extraction methods were observed .

Conclusion:

The accurate identification of 14 genera showed the reliability of MALDI-TOF MS as an optional methodology to the routine identification methods currently used in laboratories.

Chorioamnionitis due to Leptotrichia trevisanii

Very long fusiform gram-negative bacilli were observed after Gram staining of amniotic fluid from a 36-year-old multigravida woman. At 24 hours, pure, abundant growth of smooth, gray, only slightly convex catalase-positive and oxidase-negative colonies measuring about 2 mm were observed. Growth was greater in anaerobic than in aerobic conditions. The bacterium was identified as Leptotrichia trevisanii by matrix-assisted laser desorption ionization time of flight mass spectrometry. Ampicillin and gentamicin were prescribed for chorioamnionitis, and vaginal prostaglandins were administered to terminate the pregnancy. The patient remained afebrile throughout 48 hours and was discharged. Microscopic examination of the placenta revealed severe acute chorioamnionitis with a maternal inflammatory response and abundant bacillary-shaped microorganisms. To our knowledge, this isolate constitutes the first reported case of chorioamnionitis caused by L. trevisanii.

Leptotrichia species in human infections II

Leptotrichia species are non-motile facultative anaerobic/anaerobic bacteria that are found mostly in the oral cavity and some other parts of the human body, in animals, and even in ocean sediments. Valid species include L. buccalis, L. goodfellowii, L. hofstadii, L. honkongensis, L. shahii, L. trevisanii, and L. wadei. Some species require serum or blood for growth. All species ferment carbohydrates and produce lactic acid that may be involved with tooth decay. Acting as opportunistic pathogens, they are involved in a variety of diseases, and have been isolated from immunocompromised but also immunocompetent individuals. Mucositis, oral lesions, wounds, and abscesses may predispose to Leptotrichia septicemia. Because identification of Leptotrichia species by phenotypic features occasionally lead to misidentification, genetic techniques such as 16S rRNA gene sequencing is recommended. Early diagnosis and treatment of leptotrichia infections is important for positive outcomes. Over the last years, Leptotrichia species have been associated with several changes in taxonomy and new associations with clinical diseases. Such changes are reported in this updated review.