Statement of problem The maxillary lateral incisor is often congenitally missing in patients with a cleft palate. The congenital cleft presents the practitioner with challenges including quantity and quality of bone, a surgically managed cleft correction, and limited clinical space. Purpose The purpose of this investigation was to calculate the 5-year success and survival rate of narrow-diameter implants used to restore a missing lateral incisor in patients with a cleft palate. Material and methods Fourteen study participants with a cleft palate and a missing maxillary lateral incisor were enrolled based on established criteria. Seventeen narrow-diameter implants (AstraTech OsseoSpeed 3.0S and OsseoSpeed TX 3.5 mm) were placed using a 2-stage protocol and restored with a custom titanium abutment and a cement-retained crown. Clinical and radiographic examinations were performed annually for 5 years. Four probe depth measurements were measured and evaluated using an analysis of covariance (ANCOVA) with Tukey-Kramer multiple comparisons tests. Radiographic marginal bone loss was measured annually using a digital subtraction technique and evaluated with ANCOVA, and the least square mean was derived. The restoration was evaluated using Pink (PES) and White (WES) Esthetic scores. Results Regarding probing depth measurements, a significant variance was found between the 4 locations (P<.001), and a linear effect of year was also found (P=.005). The multiple comparisons tests showed the mean buccal probe depth was lower compared with the mean at each of the other 3 locations (P≤.039) from baseline to 5-year follow-up. The least square mean ±standard deviation of the marginal bone loss over the 5-year entire study was 0.55 ±0.088 mm. Regarding prosthesis evaluation, the mean score for PES was 6.15 and 6.63 for the WES with a maximum score of 10. The level for clinical acceptance was set at a total score of 6. To meet the criteria for success over the 5-year period, no more than 2.3 mm of total bone loss was acceptable. The number of implants that met the criteria for success at 5 years was 92%. Regarding survival, the number of implants still in place, functional, and asymptomatic at 5 years was 100%. Conclusions Based on the findings, the peri-implant soft tissue probe depths exhibited significant change during the 5-year investigation. Regarding esthetic outcomes, single tooth NDI for replacing a lateral incisor in the cleft patient is a clinically acceptable treatment. Narrow-diameter implants may be a reliable treatment for replacing a missing lateral incisor in patients with a cleft at 5-year follow-up with an implant survival rate of 100% and a success rate of 92%.

IntroductionPhosphorus (P) deficiency in plants creates a variety of metabolic perturbations that decrease photosynthesis and growth. Phosphorus deficiency is especially challenging for the production of bioenergy feedstock plantation species, such as poplars (Populus spp.), where fertilization may not be practically or economically feasible. While the phenotypic effects of P deficiency are well known, the molecular mechanisms underlying whole-plant and tissue-specific responses to P deficiency, and in particular the responses of commercially valuable hardwoods, are less studied. MethodsWe used a multi-tissue and multi-omics approach using transcriptomic, proteomic, and metabolomic analyses of the leaves and roots of black cottonwood (Populus trichocarpa) seedlings grown under P-deficient (5 µM P) and replete (100 µM P) conditions to assess this knowledge gap and to identify potential gene targets for selection for P efficiency.ResultsIn comparison to seedlings grown at 100 µM P, P-deficient seedlings exhibited reduced dry biomass, altered chlorophyll fluorescence, and reduced tissue P concentrations. In line with these observations, growth, C metabolism, and photosynthesis pathways were downregulated in the transcriptome of the P-deficient plants. Additionally, we found evidence of strong lipid remodeling in the leaves. Metabolomic data showed that the roots of P-deficient plants had a greater relative abundance of phosphate ion, which may reflect extensive degradation of P-rich metabolites in plants exposed to long-term P-deficiency. With the notable exception of the KEGG pathway for Starch and Sucrose Metabolism (map00500), the responses of the transcriptome and the metabolome to P deficiency were consistent with one another. No significant changes in the proteome were detected in response to P deficiency.Discussion and conclusionCollectively, our multi-omic and multi-tissue approach enabled the identification of important metabolic and regulatory pathways regulated across tissues at the molecular level that will be important avenues to further evaluate for P efficiency. These included stress-mediating systems associated with reactive oxygen species maintenance, lipid remodeling within tissues, and systems involved in P scavenging from the rhizosphere.

Host-microbiome interactions are known to have substantial effects on human health, but the diversity of the human microbiome makes it difficult to definitively attribute specific microbiome features to a host phenotype. One approach to overcoming this challenge is to use animal models of host-microbiome interaction, but it must be determined that relevant aspects of host-microbiome interactions are reflected in the animal model. One such experimental validation is an experiment by Ridura et al. In that experiment, transplanting a microbiome from a human into a mouse also conferred the human donor's obesity phenotype. We have aggregated a collection of previously published host-microbiome mouse-model experiments and combined it with thousands of sequenced and annotated bacterial genomes and metametabolomic pathways. Three computational models were generated, each model reflecting an aspect of host-microbiome interactions: 1) Predict the change in microbiome community structure in response to host diet using a community interaction network, 2) Predict metagenomic data from microbiome community structure, and 3) Predict host obesogenesis from modeled microbiome metagenomic data. These computationally validated models were combined into an integrated model of host-microbiome-diet interactions and used to replicate the Ridura experiment in silico. The results of the computational models indicate that network-based models are significantly more predictive than similar but non-network-based models. Network-based models also provide additional insight into the molecular mechanisms of host-microbiome interaction by highlighting metabolites and metabolic pathways proposed to be associated with microbiome-based obesogenesis. While the models generated in this study are likely too specific to the animal models and experimental conditions used to train our models to be of general utility in a broader understanding of obesogenesis, the approach detailed here is expected to be a powerful tool of investigating multiple types of host-microbiome interactions.

Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida KT2440, an important organism for bioproduction. We performed independent component analysis of a compendium of 321 high-quality gene expression profiles, which were previously published or newly generated in this study. We identified 84 groups of independently modulated genes (iModulons) that explain 75.7% of the total variance in the compendium. With these iModulons, we (i) expand our understanding of the regulatory functions of 39 iModulon associated TFs (e.g., HexR, Zur) by systematic comparison with 1993 previously reported TF-gene interactions; (ii) outline transcriptional changes after the transition from the exponential growth to stationary phases; (iii) capture group of genes required for utilizing diverse carbon sources and increased stationary response with slower growth rates; (iv) unveil multiple evolutionary strategies of transcriptome reallocation to achieve fast growth rates; and (v) define an osmotic stimulon, which includes the Type VI secretion system, as coordination of multiple iModulon activity changes. Taken together, this study provides the first quantitative genome-scale TRN for P. putida KT2440 and a basis for a comprehensive understanding of its complex transcriptome changes in a variety of physiological states.

Bone marrow aspirate concentrate (BMAC) is a potentially useful biological product for bone regeneration. This study investigated whether BMAC can be enriched by local minor corticotomies. Five 4-month-old domestic pigs were used with each pig undergoing two minor corticotomies at one randomly-selected tibia. Two weeks after the operation, bone marrow was aspirated from both tibiae and processed into BMAC samples. The amount of mesenchymal stem cells (MSCs) and the concentration of several regenerative growth factors contained in BMAC, as well as the proliferative and osteogenic differentiation capacity of MSCs, were compared between the corticotomy and the control sides. Another four weeks later, healing of the corticotomies was evaluated by radiographic and histological methods. The results demonstrated that BMAC from the corticotomy side contained significantly more MSCs than the control side. MSCs from the corticotomy side also proliferated significantly faster and tended to have stronger osteogenic differentiation than those from the control side. In contrast, the protein concentration of TGF-β, BMP-2 and PDGF contained in BMAC was only minimally changed by the corticotomies. The corticotomies in all pigs healed uneventfully, showing complete obliteration of the corticotomy gaps on CT images. Comparison between the two sides showed that the corticotomy side had thicker and denser cortical bone and more abundant osteogenic cell differentiation than the control side. These findings suggest that the quantity and proliferative/osteogenic differentiation capacity of MSCs contained in local BMAC can be enhanced by minor corticotomies, and spontaneous healing of the corticotomy can be completed within 6 weeks of the operation.

Dentists prescribe 10% of all outpatient antibiotic prescriptions, writing more than 25.7 million prescriptions per year. Many are for prophylaxis in patients with prosthetic joint replacements; the American Dental Society states that "in general," prophylactic antibiotics are not recommended to prevent prosthetic joint infections. Orthopedic surgeons are concerned with the risk of implant infections following a dental procedure and, therefore, see high value and low risk in recommending prophylaxis. Patients are "stuck in the middle," with conflicting recommendations from orthopedic surgeons (OS) and dentists. Unnecessary prophylaxis and fear of lawsuits amongst private practice dentists and OS has not been addressed. We review The American Heart Association/American College of Cardiology, American Dental Association, and American Association of Orthopedic Surgeons' guidelines on dental antibiotic prophylaxis for the prevention of endocarditis and prosthetic joint infections. We provide experience on how to engage private-practice dentists and OS in dental stewardship using a community-based program.

BACKGROUND:Plants, fungi, and bacteria form complex, mutually-beneficial communities within the soil environment. In return for photosynthetically derived sugars in the form of exudates from plant roots, the microbial symbionts in these rhizosphere communities provide their host plants access to otherwise inaccessible nutrients in soils and help defend the plant against biotic and abiotic stresses. One role that bacteria may play in these communities is that of Mycorrhizal Helper Bacteria (MHB). MHB are bacteria that facilitate the interactions between plant roots and symbiotic mycorrhizal fungi and, while the effects of MHB on the formation of plant-fungal symbiosis and on plant health have been well documented, the specific molecular mechanisms by which MHB drive gene regulation in plant roots leading to these benefits remain largely uncharacterized.RESULTS:Here, we investigate the effects of the bacterium Pseudomonas fluorescens SBW25 (SBW25) on aspen root transcriptome using a tripartite laboratory community comprised of Populus tremuloides (aspen) seedlings and the ectomycorrhizal fungus Laccaria bicolor (Laccaria). We show that SBW25 has MHB activity and promotes mycorrhization of aspen roots by Laccaria. Using transcriptomic analysis of aspen roots under multiple community compositions, we identify clusters of co-regulated genes associated with mycorrhization, the presence of SBW25, and MHB-associated functions, and we generate a combinatorial logic network that links causal relationships in observed patterns of gene expression in aspen seedling roots in a single Boolean circuit diagram. The predicted regulatory circuit is used to infer regulatory mechanisms associated with MHB activity.CONCLUSIONS:In our laboratory conditions, SBW25 increases the ability of Laccaria to form ectomycorrhizal interactions with aspen seedling roots through the suppression of aspen root antifungal defense responses. Analysis of transcriptomic data identifies that potential molecular mechanisms in aspen roots that respond to MHB activity are proteins with homology to pollen recognition sensors. Pollen recognition sensors integrate multiple environmental signals to down-regulate pollenization-associated gene clusters, making proteins with homology to this system an excellent fit for a predicted mechanism that integrates information from the rhizosphere to down-regulate antifungal defense response genes in the root. These results provide a deeper understanding of aspen gene regulation in response to MHB and suggest additional, hypothesis-driven biological experiments to validate putative molecular mechanisms of MHB activity in the aspen-Laccaria ectomycorrhizal symbiosis.

In vitro culture and gene expression. (ZIP 1530 kb)

Bacterial biofilm formation involves signaling and regulatory pathways that control the transition from motile to sessile lifestyle, production of extracellular polymeric matrix, and maturation of the biofilm 3D structure. Biofilms are extensively studied because of their importance in biomedical, ecological and industrial settings. Gene inactivation is a powerful approach for functional studies but it is often labor intensive, limiting systematic gene surveys to the most tractable bacterial hosts. Here, we adapted the CRISPR interference (CRISPRi) system for use in diverse strain isolates of P. fluorescens, SBW25, WH6 and Pf0-1. We found that CRISPRi is applicable to study complex phenotypes such as cell morphology, motility and biofilm formation over extended periods of time. In SBW25, CRISPRi-mediated silencing of genes encoding the GacA/S two-component system and regulatory proteins associated with the cylic di-GMP signaling messenger produced swarming and biofilm phenotypes similar to those obtained after gene inactivation. Combined with detailed confocal microscopy of biofilms, our study also revealed novel phenotypes associated with extracellular matrix biosynthesis as well as the potent inhibition of SBW25 biofilm formation mediated by the PFLU1114 operon. We conclude that CRISPRi is a reliable and scalable approach to investigate gene networks in the diverse P. fluorescens group.

Lichens, encompassing 20,000 known species, are symbioses between specialized fungi (mycobionts), mostly ascomycetes, and unicellular green algae or cyanobacteria (photobionts). Here we describe the first parallel genomic analysis of the mycobiont Cladonia grayi and of its green algal photobiont Asterochloris glomerata. We focus on genes/predicted proteins of potential symbiotic significance, sought by surveying proteins differentially activated during early stages of mycobiont and photobiont interaction in coculture, expanded or contracted protein families, and proteins with differential rates of evolution. A) In coculture, the fungus upregulated small secreted proteins, membrane transport proteins, signal transduction components, extracellular hydrolases and, notably, a ribitol transporter and an ammonium transporter, and the alga activated DNA metabolism, signal transduction, and expression of flagellar components. B) Expanded fungal protein families include heterokaryon incompatibility proteins, polyketide synthases, and a unique set of G-protein α subunit paralogs. Expanded algal protein families include carbohydrate active enzymes and a specific subclass of cytoplasmic carbonic anhydrases. The alga also appears to have acquired by horizontal gene transfer from prokaryotes novel archaeal ATPases and Desiccation-Related Proteins. Expanded in both symbionts are signal transduction components, ankyrin domain proteins and transcription factors involved in chromatin remodeling and stress responses. The fungal transportome is contracted, as are algal nitrate assimilation genes. C) In the mycobiont, slow-evolving proteins were enriched for components involved in protein translation, translocation and sorting. The surveyed genes affect stress resistance, signaling, genome reprogramming, nutritional and structural interactions. The alga carries many genes likely transferred horizontally through viruses, yet we found no evidence of inter-symbiont gene transfer. The presence in the photobiont of meiosis-specific genes supports the notion that sexual reproduction occurs in Asterochloris while they are free-living, a phenomenon with implications for the adaptability of lichens and the persistent autonomy of the symbionts. The diversity of the genes affecting the symbiosis suggests that lichens evolved by accretion of many scattered regulatory and structural changes rather than through introduction of a few key innovations. This predicts that paths to lichenization were variable in different phyla, which is consistent with the emerging consensus that ascolichens could have had a few independent origins.

Rhizosphere-associated Pseudomonas fluorescens are known plant growth promoting (PGP) and mycorrhizal helper bacteria (MHB) of many plants and ectomycorrhizal fungi. We investigated the spatial and temporal dynamics of colonization of mycorrhizal and non-mycorrhizal Aspen seedlings roots by the P. fluorescens strains SBW25, WH6, Pf0-1, and the P. protegens strain Pf-5. Seedlings were grown in laboratory vertical plates systems, inoculated with a fluorescently labeled Pseudomonas strain, and root colonization was monitored over a period of 5 weeks. We observed unexpected diversity of bacterial assemblies on seedling roots that changed over time and were strongly affected by root mycorrhization. P. fluorescens SBW25 and WH6 stains developed highly structured biofilms with internal void spaces forming channels. On mycorrhizal roots bacteria appeared encased in a mucilaginous substance in which they aligned side by side in parallel arrangements. The different phenotypic classes of bacterial assemblies observed for the four Pseudomonas strains were summarized in a single model describing transitions between phenotypic classes. Our findings also reveal that bacterial assembly phenotypes are driven by interactions with mucilaginous materials present at roots.

Bacteria are not simply passive consumers of nutrients or merely steady-state systems. Rather, bacteria are active participants in their environments, collecting information from their surroundings and processing and using that information to adapt their behavior and optimize survival. The bacterial regulome is the set of physical interactions that link environmental information to the expression of genes by way of networks of sensors, transporters, signal cascades, and transcription factors. As bacteria cannot have one dedicated sensor and regulatory response system for every possible condition that they may encounter, the sensor systems must respond to a variety of overlapping stimuli and collate multiple forms of information to make "decisions" about the most appropriate response to a specific set of environmental conditions. Here, we analyze Pseudomonas fluorescens transcriptional responses to multiple sulfur nutrient sources to generate a predictive, computational model of the sulfur regulome. To model the regulome, we utilize a transmitter-channel-receiver scheme of information transfer and utilize principles from information theory to portray P. fluorescens as an informatics system. This approach enables us to exploit the well-established metrics associated with information theory to model the sulfur regulome. Our computational modeling analysis results in the accurate prediction of gene expression patterns in response to the specific sulfur nutrient environments and provides insights into the molecular mechanisms of Pseudomonas sensory capabilities and gene regulatory networks. In addition, modeling the bacterial regulome using the tools of information theory is a powerful and generalizable approach that will have multiple future applications to other bacterial regulomes. IMPORTANCE Bacteria sense and respond to their environments using a sophisticated array of sensors and regulatory networks to optimize their fitness and survival in a constantly changing environment. Understanding how these regulatory and sensory networks work will provide the capacity to predict bacterial behaviors and, potentially, to manipulate their interactions with an environment or host. Leveraging the information theory provides useful quantitative metrics for modeling the information processing capacity of bacterial regulatory networks. As our model accurately predicted gene expression profiles in a bacterial model system, we posit that the information theory-based approaches will be important to enhance our understanding of a wide variety of bacterial regulomes and our ability to engineer bacterial sensory and regulatory networks.

Diverse communities of bacteria colonize plant roots and the rhizosphere. Many of these rhizobacteria are symbionts and provide plant growth promotion (PGP) services, protecting the plant from biotic and abiotic stresses and increasing plant productivity by providing access to nutrients that would otherwise be unavailable to roots. In return, these symbiotic bacteria receive photosynthetically-derived carbon (C), in the form of sugars and organic acids, from plant root exudates. PGP activities have been characterized for a variety of forest tree species and are important in C cycling and sequestration in terrestrial ecosystems. The molecular mechanisms of these PGP activities, however, are less well-known. In a previous analysis of Pseudomonas genomes, we found that the bacterial transportome, the aggregate activity of a bacteria's transmembrane transporters, was most predictive for the ecological niche of Pseudomonads in the rhizosphere. Here, we used Populus tremuloides Michx. (trembling aspen) seedlings inoculated with one of three Pseudomonas fluorescens strains (Pf0-1, SBW25, and WH6) and one Pseudomonas protegens (Pf-5) as a laboratory model to further investigate the relationships between the predicted transportomic capacity of a bacterial strain and its observed PGP effects in laboratory cultures. Conditions of low nitrogen (N) or low phosphorus (P) availability and the corresponding replete media conditions were investigated. We measured phenotypic and biochemical parameters of P tremuloides seedlings and correlated P fluorescens strain-specific transportomic capacities with P tremuloides seedling phenotype to predict the strain and nutrient environment-specific transporter functions that lead to experimentally observed, strain, and media-specific PGP activities and the capacity to protect plants against nutrient stress. These predicted transportomic functions fall in three groups: (i) transport of compounds that modulate aspen seedling root architecture, (ii) transport of compounds that help to mobilize nutrients for aspen roots, and (iii) transporters that enable bacterial acquisition of C sources from seedling root exudates. These predictions point to specific molecular mechanisms of PGP activities that can be directly tested through future, hypothesis-driven biological experiments.

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root-mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensor systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with 15 transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and jasmonic acid. This multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.

Objective. Transconjunctival approach to the lower one-third of the orbit is commonly used to avoid transcutaneous incisions when surgical access is needed. A lateral canthotomy is used in conjunction with this approach if increased lateral exposure is required. A major disadvantage to lateral canthotomy is difficulty in resuspension of the lateral canthal tendon, which can lead to unaesthetic outcomes. The present report describes two cases of lateral tarsal incision or, as we decided to call it, the "lateral tarsotomy" technique. This simple approach is used to increase lateral access to the orbit without the need for lateral canthotomy.Study Design. Two patients presented with internal orbital wall trauma that required repair; access was achieved with a transconjunctival approach in conjunction with lateral tarsotomy. The patients were followed up at 1 week, 1 month, and 3 months to document the development of possible unaesthetic and poor functional outcomes.Results. Excellent cosmetic results were observed, with no noticeable deformity at the tarsotomy site. There was no evidence of ectropion, entropion, scleral show, and visible scars.Conclusions. The above results suggest that the lateral tarsotomy approach is a practical alternative to lateral canthotomy when increased lateral exposure is required.

Background: Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. However, the community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome's interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependent on its community metabolome; an emergent property of the microbiome.Results: Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles.Conclusions: Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome-host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.

The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. However, new algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad's ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter of plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism's transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbial ecology. The framework developed here can be generalized to the analysis of any bacteria across a wide range of environments and ecological niches making this approach a powerful tool for providing insights into functional predictions from bacterial genomic data.