Multiple bacterial partners in symbiosis with the nudibranch mollusk Rostanga alisae

The discovery of symbiotic associations extends our understanding of the biological diversity in the aquatic environment and their impact on the host’s ecology. Of particular interest are nudibranchs that unprotected by a shell and feed mainly on sponges. The symbiotic association of the nudibranch Rostanga alisae with bacteria was supported by ample evidence, including an analysis of cloned bacterial 16S rRNA genes and a fluorescent in situ hybridization analysis, and microscopic observations. A total of 74 clones belonging to the phyla α-, β-, γ-Proteobacteria, Actinobacteria, and Cyanobacteria were identified. FISH confirmed that bacteriocytes were packed with Bradyrhizobium, Maritalea, Labrenzia, Bulkholderia, Achromobacter, and Stenotrophomonas mainly in the foot and notum epidermis, and also an abundance of Synechococcus cyanobacteria in the intestinal epithelium. An ultrastructural analysis showed several bacterial morphotypes of bacteria in epidermal cells, intestine epithelium, and in mucus layer covering the mollusk body. The high proportion of typical bacterial fatty acids in R. alisae indicated that symbiotic bacteria make a substantial contribution to its nutrition. Thus, the nudibranch harbors a high diversity of specific endo- and extracellular bacteria, which previously unknown as symbionts of marine invertebrates that provide the mollusk with essential nutrients. They can provide chemical defense against predators.

Bacterial Morphotypes as Important Trait for Uropathogenic E. coli Diagnostic; a Virulence-Phenotype-Phylogeny Study

Urinary tract infections (UTIs) belong to the most common pathologies in Mexico and are mainly caused by Uropathogenic Escherichia coli (UPEC). UPEC possesses a wide diversity of virulence factors that allow it to carry out its pathogenesis mechanism in the urinary tract (UT). The development of morphotypes in UT represents an important feature of UPEC because it is associated with complications in diagnosis of UTI. The aim of this study was to determine the presence of bacterial morphotypes, virulence genes, virulence phenotypes, antibiotic resistant, and phylogenetic groups in clinical isolates of UPEC obtained from women in Sonora, Mexico. Forty UPEC isolates were obtained, and urine morphotypes were observed in 65% of the urine samples from where E. coli was isolated. Phylogenetic group B2 was the most prevalent. The most frequent virulence genes were fimH (100%), fliCD (90%), and sfaD/focC (72%). Biofilm formation (100%) and motility (98%) were the most prevalent phenotypes. Clinical isolates showed high resistance to aminoglycosides and β-lactams antibiotics. These data suggest that the search for morphotypes in urine sediment must be incorporated in the urinalysis procedure and also that clinical isolates of UPEC in this study can cause upper, lower, and recurrent UTI.

Bacterial morphotypes as biodiversity indicators in a scarcely explored ecosystem in Santiago de Cali, Colombia

Bacteria are considered as the most diverse microorganisms on earth. However, bacterial diversity is unknown in some ecosystems, such as leachate treatment plants. In the present study, we characterized culturable bacteria isolated from six lagoons and one pure leachate to assess whether bacterial morphotypes can be used as biodiversity indicators. The sampling site was a leachate treatment plant located in Santiago de Cali. Overall, 311 bacterial morphotypes were collected from six lagoons, and a pure landfill leachate, and were identified using colony characters. Four biodiversity indexes related to species richness and abundance as well as to the estimation of the number of species present were calculated. The results show a great diversity of bacterial morphotypes in all samples. Further, the highest estimates of biodiversity were observed at lagoon 6 physicochemically treated, and the lowest estimates were observed at lagoons 5 and 8. The leachate generated in the sampled lagoons, which were composed of different elements, allows for the colonization of diverse bacteria. Moreover, these bacteria were resistant to the treatment plant processes, thereby explaining the highest diversity observed at the lagoon 6. Our results showed that bacterial morphotypes can be used as biodiversity indicators in ecosystems.

Deep Neural Networks Offer Morphologic Classification and Diagnosis of Bacterial Vaginosis

Background: Bacterial vaginosis (BV) is caused by the excessive and imbalanced growth of bacteria in vagina, affecting 30-50% of women in their lives. Gram stain followed by Nugent scoring based on bacterial morphotypes under the microscope (NS) has been considered the golden standard for BV diagnosis, which is often labor-intensive, time-consuming, and variable results from person to person. Methods: We developed and optimized a convolutional neural networks (CNN) model, and evaluated its ability to automatically identify and classify three categories of Nugent scores from microscope images. The CNN model was first established with a panel of microscopic images with Nugent scores determined by experts. The model was trained by minimizing the cross entropy loss function and optimized by using a momentum optimizer. The separate test sets of images collected from three hospitals were evaluated by the CNN models. Results: The CNN model consisted of 25 convolutional layers, 2 pooling layers, and a fully connected layer. The model obtained 82.4% sensitivity and 96.6% specificity on the 5,815 validation images when considered altered vaginal flora and BV as the positive samples, which was better than the top-level technologists and obstetricians in China. The ability of generalization for our model was strong that it obtained 75.1% accuracy of three categories of Nugent scores on the independent test set of 1082 images, which was 6.6% higher than the average of three technologists, who are with a bachelor degree in medicine and eligible making diagnostic decisions. When three technologists ran one specimen in triplicate, the precision of three categories of Nugent scores was 54.0%. 103 samples diagnosed by two technologists at different days showed repeatability of 90.3%. Conclusion: The CNN model over-performed human healthcare practitioners on accuracy and stability for three categories of Nugent scores diagnosis. The deep learning model may offer translational applications in automating diagnosis of bacterial vaginosis with proper supporting hardware.

Morphologic Classification and Automatic Diagnosis of Bacterial Vaginosis by Deep Neural Networks

BackgroundBacterial vaginosis (BV) was the most common condition for women’s health caused by the disruption of normal vaginal flora and an overgrowth of certain disease-causing bacteria, affecting 30-50% of women at some time in their lives. Gram stain followed by Nugent scoring (NS) based on bacterial morphotypes under the microscope was long considered golden standard for BV diagnosis. This conventional manual method was often considered labor intensive, time consuming, and variable results from person to person.MethodsWe developed four convolutional neural networks (CNN) models, and evaluated their ability to automatic identify vaginal bacteria and classify Nugent scores from microscope images. All the CNN models were first trained with 23280 microscopic images labeled with Nugent scores from top experts. A separate set of 5815 images were evaluated by the CNN models. The best CNN model was selected to generalize its application on an independent sets of 1082 images collecting from three teaching hospitals. Different hardwares were used to take images in hospitals.ResultsOur model could classify three Nugent Scores from images with high three classification accuracy of 89.3% (with 82.4% sensitivity and 96.6% specificity) on the 5815 test images, which was better diagnostic yield than the top-level technologists and obstetricians in China. The ability of generalization for our model was strong that it obtained 75.1%, which was 6.6% higher than the average of technologists.ConclusionThe CNN model over performed human healthcare practitioners on accuracy, efficiency and stability for BV diagnosis using microscopic image-based Nugent scores. The deep learning model may offer translational application in automating diagnosis of bacterial vaginosis with proper supporting hardware.

Five new species of Homoscleromorpha (Porifera) from the Caribbean Sea and re-description ofPlakina jamaicensis

Five new species of Homoscleromorpha (Porifera) of four genera,Oscarella,Plakortis,PlakinaandCorticium, are described from vertical walls of reef caves at depths ranging from 23 to 28 m in the Caribbean Sea.Oscarella nathaliaesp. nov. has a leaf-like thinly encrusting, flat body, loosely attached to the substrate and a perforated, not lobate surface.Oscarella nathaliaesp. nov. contains two bacterial morphotypes and is characterized by two mesohylar cell types with inclusions.Plakortis myraesp. nov. has diods of two categories: abundant large ones (83–119 μm long) and rare small ones (67–71 μm long) with sinuous, S-bent centres; triods Y- or T-shaped (18–5 μm long), and abundant microrhabds (5–12 μm long).Plakortis edwardsisp. nov. has diods of one category with thick, sinuous, S-bent centres (110 to 128 μm long); triods T-shaped (actines 28–59 μm long). It is the only species of this genus showing small diods (22–31 μm long).Plakortis dariaesp. nov. has diods of two categories: large ones (67–112 μm long) and small, rare, irregular ones, slightly curved, often deformed with one end blunt (30–59 μm long); triods rare and regular (actines 20–44 μm long).Corticium diamantensesp. nov. has oscula situated near its border, regular non-lophose calthrops of one size-class, very rare tetralophose calthrops and candelabra with the fourth actine ramified basally in 4–5 microspined rays. In addition, a re-description ofPlakina jamaicensisis based on newly collected material and the type specimen.Plakortis jamaicensishas a convoluted brain-like surface; well developed sub-ectosomal cavities; irregular sinuous diods, triods, calthrops, rare monolophose calthrops, rare dilophose calthrops, rare trilophose calthrops and common tetralophose calthrops. Molecular ‘barcoding’ sequences for mitochondrial cob are given forPlakortis edwardsisp. nov.,P. dariaesp. nov.,Plakina jamaicensisandCorticium diamantensesp. nov. An identification key for all western Atlantic Homoscleromorpha is provided.

A Novel Algorithm for the Determination of Bacterial Cell Volumes That is Unbiased by Cell Morphology

The determination of cell volumes and biomass offers a means of comparing the standing stocks of auto- and heterotrophic microbes of vastly different sizes for applications including the assessment of the flux of organic carbon within aquatic ecosystems. Conclusions about the importance of particular genotypes within microbial communities (e.g., of filamentous bacteria) may strongly depend on whether their contribution to total abundance or to biomass is regarded. Fluorescence microscopy and image analysis are suitable tools for determining bacterial biomass that moreover hold the potential to replace labor-intensive manual measurements by fully automated approaches. However, the current approaches to calculate bacterial cell volumes from digital images are intrinsically biased by the models that are used to approximate the morphology of the cells. Therefore, we developed a generic contour based algorithm to reconstruct the volumes of prokaryotic cells from two-dimensional representations (i.e., microscopic images) irrespective of their shape. Geometric models of commonly encountered bacterial morphotypes were used to verify the algorithm and to compare its performance with previously described approaches. The algorithm is embedded in a freely available computer program that is able to process both raw (8-bit grayscale) and thresholded (binary) images in a fully automated manner.

Production and characterization of scum and its role in odour control in UASB reactors treating domestic wastewater

There are few studies in the literature that have aimed at characterizing the physical, chemical, and microbial aspects of scum produced in UASB reactors. In addition, there is little information on the influence of operational conditions of UASB reactors on scum formation, and the present work addresses these issues. Three demo-scale UASB reactors, fed on domestic wastewater, were employed to monitor the formation and its characteristics. Scum production was periodically assessed during different operational phases, and its characterization involved analyses of BOD, COD, solids, sulfide, sulfate, microscopic observations, as well as biodegradability tests. The results show that the scum formed was physically, chemically, and microscopically similar in both geminated reactors, being comprised mainly of organic material of low biodegradability. Several bacterial morphotypes, mainly filaments and rods, with internal sulfur granules, were observed, and the aerobic microorganisms that developed at the scum layer as a result of photosynthetic activity of cyanobacteria, seemed to play an important role in sulfide removal and odour control. Scum production rates were similar in both reactors, but the imposed higher upflow velocities resulted in a higher production rate and in a reduced biodegradability of the scum.