Moraxella oculi sp. nov., isolated from a cow with infectious bovine keratoconjunctivitis.

A novel species of the genus Moraxella was isolated from an ocular swab from a cow with infectious bovine keratoconjunctivitis. 16S rRNA gene sequencing suggested this species was Moraxella bovis (99.59 % nucleotide identity). Average nucleotide identity was calculated using a draft whole genome sequence of this strain compared with type strains of closely related Moraxella species and results established that it represents a new species. The genome size was 2 006 474 nucleotides and the G+C content was 42.51 mol%. The species could not be identified by matrix assisted laser desorption/ionization-time of flight mass spectrometry using a commercial database, confirming the novelty of the strain. We propose the name Moraxella oculi sp. nov. for this new species. The type strain is Tifton1T and has been deposited into the American Type Culture Collection (TSD-373T) and the National Collection of Type Cultures (NCTC), UK Health Security Agency (NCTC 14942T).

Alterations to the bovine bacterial ocular surface microbiome in the context of infectious bovine keratoconjunctivitis.

BACKGROUND: Infectious bovine keratoconjunctivitis (IBK) is a common cause of morbidity in cattle, resulting in significant economic losses. This study aimed to characterize the bovine bacterial ocular surface microbiome (OSM) through conjunctival swab samples from Normal eyes and eyes with naturally acquired, active IBK across populations of cattle using a three-part approach, including bacterial culture, relative abundance (RA, 16 S rRNA gene sequencing), and semi-quantitative random forest modeling (real-time polymerase chain reaction (RT-PCR)). RESULTS: Conjunctival swab samples were obtained from eyes individually classified as Normal (n = 376) or IBK (n = 228) based on clinical signs. Cattle unaffected by IBK and the unaffected eye in cattle with contralateral IBK were used to obtain Normal eye samples. Moraxella bovis was cultured from similar proportions of IBK (7/228, 3.07%) and Normal eyes (1/159, 0.63%) (p = 0.1481). Moraxella bovoculi was cultured more frequently (p < 0.0001) in IBK (59/228, 25.88%) than Normal (7/159, 4.40%) eyes. RA (via 16 S rRNA gene sequencing) of Actinobacteriota was significantly higher in Normal eyes (p = 0.0045). Corynebacterium variabile and Corynebacterium stationis (Actinobacteriota) were detected at significantly higher RA (p = 0.0008, p = 0.0025 respectively) in Normal eyes. Rothia nasimurium (Actinobacteriota) was detected at significantly higher RA in IBK eyes (p < 0.0001). Alpha-diversity index was not significantly different between IBK and Normal eyes (p > 0.05). Alpha-diversity indices for geographic location (p < 0.001), age (p < 0.0001), sex (p < 0.05) and breed (p < 0.01) and beta-diversity indices for geographic location (p < 0.001), disease status (p < 0.01), age (p < 0.001), sex (p < 0.001) and breed (p < 0.001) were significantly different between groups. Modeling of RT-PCR values reliably categorized the microbiome of IBK and Normal eyes; primers for Moraxella bovoculi, Moraxella bovis, and Staphylococcus spp. were consistently the most significant canonical variables in these models. CONCLUSIONS: The results provide further evidence that multiple elements of the bovine bacterial OSM are altered in the context of IBK, indicating the involvement of a variety of bacteria in addition to Moraxella bovis, including Moraxella bovoculi and R. nasimurium, among others. Actinobacteriota RA is altered in IBK, providing possible opportunities for novel therapeutic interventions. While RT-PCR modeling provided limited further support for the involvement of Moraxella bovis in IBK, this was not overtly reflected in culture or RA results. Results also highlight the influence of geographic location and breed type (dairy or beef) on the bovine bacterial OSM. RT-PCR modeling reliably categorized samples as IBK or Normal.

Sphingolipidomics of Bovine Pink Eye: A Pilot Study.

Sphingolipids are essential structural components of tear film that protect the surface of the eye from dehydration. A detailed analysis of the effects of pink eye infections on the sphingolipidome in cattle has not previously been undertaken. We recently published a new assay utilizing high-resolution mass spectrometric monitoring of the chloride adducts of sphingolipids that provides enhanced sensitivity and specificity. Utilizing this assay, we monitored decreases in the levels of tear film ceramides with short-chain fatty acids, hydroxy-ceramides, phytoceramides, and hydroxy-phytoceramides. Dihydroceramide levels were unaltered and increased levels of ceramides with long-chain fatty acids (24:0 and 24:1) were monitored in cattle with pink eye. The data from this pilot study (n = 8 controls and 8 pink eye) demonstrate a major disruption of the lipid tear film layer in pink eye disease, that can result in severe eye irritation and damage.

Moisture content monitoring in industrial-scale composting systems using low-cost sensor-based machine learning techniques.

Moisture is a key aspect for proper composting, allowing greater efficiency and lower environmental impact. Low-cost real-time moisture determination methods are still a challenge in industrial composting processes. The aim of this study was to design a model of hardware and software that would allow self-adjustment of a low-cost capacitive moisture sensor. Samples of organic composts with distinct waste composition and from different composting stages were used. Machine learning techniques were applied for self-adjustment of the sensor. To validate the model, results obtained in a laboratory by the gravimetric method were used. The proposed model proved to be efficient and reliable in measuring moisture in compost, reaching a correlation coefficient of 0.9939 between the moisture content verified by gravimetric analysis and the prediction obtained by the Sensor Node.

EGFRisopred: a machine learning-based classification model for identifying isoform-specific inhibitors against EGFR and HER2.

The EGFR kinase pathway is one of the most frequently activated signaling pathways in human cancers. EGFR and HER2 are the two significant members of this pathway, which are attractive drug targets of clinical relevance in lung and breast cancer. Therefore, identifying EGFR- and HER2-specific inhibitors is one of the important challenges in cancer drug discovery. To address this issue, a dataset of 519 compounds having inhibitory activity against both the isoforms, i.e., EGFR and HER2, was collected from the literature and developed a knowledge-based computational classification model for predicting the specificity of a molecule for an isoform (EGFR/HER2) with precision. A total of seventy-two classification models using nine fingerprint types, four classifiers (IBK, NB, SMO and RF) and two different datasets (EGFR and HER2 isoform specific) were developed. It was observed that the models developed using random forest and IBK performed better for EGFR- and HER2-specific datasets, respectively. Scaffold and functional group analysis led to the identification of prevalent core and fragments in each of the datasets. The accuracy of the selected best performing models was also evaluated using the decoy dataset. We have also developed an application EGFRisopred, which integrates the best performing models and permits the user to predict the specificity of a compound as an EGFR-/HER2-specific anticancer agent. It is expected that the tool's availability as a free utility will allow researchers to identify new inhibitors against these targets important in cancer.

Bovine Immune Responses to Moraxella bovis and Moraxella bovoculi Following Vaccination and Natural or Experimental Infections.

Studies have sought to develop effective vaccines against infectious bovine keratoconjunctivitis (IBK). Most research has focused on parenterally administered vaccines against Moraxella bovis antigens; however, researchers have also included Moraxella bovoculi antigens in vaccines to prevent IBK. Critical knowledge gaps remain as to which Moraxella spp antigens might be completely protective, and whether systemic, mucosal, or both types of immune responses are required for protection against IBK associated with Moraxella spp. Immune responses to commensal Moraxella spp residing in the upper respiratory tract and eye have not been analyzed to determine if these responses control colonization or contribute to IBK.

Component Causes of Infectious Bovine Keratoconjunctivitis-Non-Moraxella Organisms in the Epidemiology of Infectious Bovine Keratoconjunctivitis.

Infectious bovine keratoconjunctivitis (IBK) is a multifactorial disease complex caused by opportunistic pathogens, classically those members of the genus Moraxella. However, IBK in some situations is associated with other potentially pathogenic agents, which include Mycoplasma bovoculi, Mycoplasma bovis, Ureaplasma diversum, bovine herpesviruses, and Chlamydia sp. Ocular infections that may resemble IBK are also caused by Listeria monocytogenes. These agents and their association with IBK are reviewed in this article.

Structural characterisation of the oligosaccharide from Moraxella bovoculi type strain 237 (ATCC BAA-1259) lipooligosaccharide.

The Gram-negative bacterium Moraxella bovoculi is associated with infectious bovine keratoconjunctivitis (IBK), colloquially known as 'pink-eye'. IBK is an extremely contagious ocular disease of cattle. We report here the structure of the oligosaccharide derived from the lipooligosaccharide from M. bovoculi type strain 237 (also known as ATCC BAA-1259T). GLC-MS and correlation NMR analysis of the oligosaccharide revealed 5 sugar residues, with a notable central branched 3,4,6-α-D-Glcp. An additional α-D-Manp was present ~30% on the sub-terminal α-D-Manp of the 4-linked branch. This oligosaccharide structure was consistent with other members of the Moraxellaceae where no heptose was present and 5-linked Kdo was directly attached to the central 3,4,6-α-D-Glcp.

Molecular characterization of bacterial microbiota associated with infectious bovine keratoconjunctivitis in Michoacán, Mexico / Caracterización molecular de la microbiota bacteriana asociada con queratoconjuntivitis infecciosa bovina en Michoacán, México / Caracterização molecular da microbiota bacteriana associada à ceratoconjuntivite bovina infecciosa em Michoacán, México

Abstract Background: The most common ocular disease affecting cattle worldwide is infectious bovine keratoconjunctivitis (IBK), which has been associated with Moraxella bovis bacterium. Objective: To report the molecular characterization of the ocular bacterial microbiota and its relation to IBK in cattle in two dairy regions in Michoacán, Mexico. Methods: A total population of 761 bovines were evaluated, of which 17 (2.23%) showed symptoms of IBK. Thirty-eight bacterial isolates from ocular samples of bovines with IBK were characterized by Gram-staining and antimicrobial sensitivity. In addition, isolates were identified by sequence comparisons of the 16S ribosomal gene. Results: The genus Moraxella was one of the most abundant bacteria and M. bovoculi was the most predominant species. Conclusion: The bacterial isolates identified in eye lesions of cattle and associated to IBK are diverse. To the author´s knowledge, this is the first study on the subject in Mexico; therefore, more research is needed to estimate the incidence of IBK and determine its associated microbiota.

Resumen Antecedentes: la enfermedad ocular más común que afecta al ganado en todo el mundo es la queratoconjuntivitis infecciosa bovina (IBK), que se ha asociado con la bacteria Moraxella bovis. Objetivo: reportar la caracterización molecular de la microbiota bacteriana ocular y su relación con IBK en ganado de dos regiones lecheras en Michoacán, México. Métodos: se evaluó una población total de 761 bovinos de los cuales 17 (2,23%) mostraron síntomas de IBK. Se obtuvieron treinta y ocho aislamientos bacterianos de muestras oculares de bovinos con IBK, los cuales se caracterizaron por tinción de Gram y sensibilidad antimicrobiana. Además, los aislamientos se identificaron mediante comparaciones de secuencias del gen ribosomal 16S. Resultados: el género Moraxella fue una de las bacterias más abundantes y M. bovoculi fue la especie más predominante. Conclusión: los aislamientos bacterianos identificados en lesiones oculares de bovinos y asociados a IBK son diversos. Hasta donde sabemos, este es el primer estudio sobre el tema realizado en México; por lo tanto, es necesario ampliar esta investigación para estimar la incidencia de IBK y determinar la microbiota asociada con la misma.

Resumo Antecedentes: a doença ocular mais comum que afeta o gado no mundo é a ceratoconjuntivite bovina (IBK), que tem sido associada à bactéria Moraxella bovis. Objetivo: relatar a caracterização molecular da microbiota bacteriana ocular e sua relação com a IBK em bovinos de duas regiões leiteiras de Michoacán, México. Métodos: foi avaliada uma população total de 761 bovinos, más apenas 17 (2,23%) apresentaram sintomas de IBK. Trinta e oito isolados bacterianos de amostras de olho bovino com IBK foram caracterizados por coloração de Gram e sensibilidade antimicrobiana. Além disso, os isolados foram identificados por comparação de sequências do gene ribossômico 16S. Resultados: a microbiota bacteriana associada à IBK foi diversa, sendo o gênero Moraxella uma das mais abundantes e M. bovoculi a espécie predominante. Conclusão: de acordo com o conhecimento dos autores, este é o primeiro estudo sobre o tema no México até o momento, portanto é necessário expandir essa pesquisa para estimar a incidência de IBK e determinar a microbiota associada à mesma.

A multiplex real-time PCR assay for the detection and differentiation of five bovine pinkeye pathogens.

Infectious bovine keratoconjunctivitis (IBK), also known as pinkeye, is one of the most common eye diseases in cattle. Several pathogens have been associated with IBK cases, however, Moraxella bovis, Moraxella bovoculi, Mycoplasma bovis, Mycoplasma bovoculi and bovine herpesvirus type 1 (BHV-1) are most frequently observed. A multiplex real-time PCR assay using two reactions was developed for the detection and differentiation of these five pathogens. Detection sensitivities of the multiplex assays were compared to singleplex reactions testing for the same targets. Correlation coefficients (R2) of >0.99, and PCR efficiencies between 92 and 106% were demonstrated in all singleplex and multiplex real-time PCR reactions. The limits of detection (LOD) of multiplex assays for Moraxella bovis, Moraxella bovoculi, Mycoplasma bovis, Mycoplasma bovoculi and BHV-1 were 19, 23, 25, 24 and 26 copies per reaction, respectively. No cross amplification was observed for specificity testing of 179 IBK positive clinical samples and 55 non-target clinical samples. Percentage of clinical samples positive for Mycoplasma bovoculi, Moraxella bovoculi, Moraxella bovis, BHV-1 and Mycoplasma bovis were 88.8% (159/179), 75.9% (136/179), 60.3% (108/179), 11.7% (21/179) and 10.0% (18/179), respectively. Moraxella bovis, Moraxella bovoculi and Mycoplasma bovoculi were more prevalent than Mycoplasma bovis and BHV-1 in IBK samples collected from animals in this study population. Our data indicates that the multiplex real-time PCR panel assay is highly sensitive and highly specific for the detection and differentiation of the five major pathogens associated with bovine pinkeye.

Tear Film Amphiphilic and Anti-Inflammatory Lipids in Bovine Pink Eye.

Background: Tear film fluid serves as a dynamic barrier that both lubricates the eye and protects against allergens and infectious agents. However, a detailed analysis of a bacteria-induced immune response on the tear film lipidome has not been undertaken. Methods: We undertook a high-resolution mass spectrometry lipidomics analysis of endogenous anti-inflammatory and structural tear film lipids in bovine pink eye. Results: Bovine pink eye resulted in dramatic elevations in tear fluid levels of the anti-inflammatory lipids resolvin E2, cyclic phosphatidic acid 16:0, and cyclic phosphatidic acid 18:0. In addition, there were elevated levels of the structural lipids (O-acyl)-ω-hydroxy-fatty acids, cholesterol sulfate, ethanolamine plasmalogens, and sphingomyelins. Lipid peroxidation also was augmented in pink eye as evidenced by the hydroperoxy derivatives of ethanolamine plasmalogens. Conclusions: Ocular infections with Moraxella bovis result in the induction of a number of endogenous anti-inflammatory lipids and augmentation of the levels of structural glycerophospholipids and sphingolipids. Increased levels of hydroperoxy glycerophospholipids also indicate that this bacterial infection results in lipid peroxidation.

Antigenic characterization of Moraxella bovis, Moraxella bovoculi and Moraxella ovis strains with potential use in vaccines.

Moraxella bovis is historically known as the primary agent of infectious bovine keratoconjunctivitis (IBK). However, Moraxella bovoculi and Moraxella ovis are also reported to be involved in the pathogenesis of IBK, therefore, these three species should be included in the development of a new vaccine with a broad-spectrum protection against the disease natural challenge. In this study we investigated the antigenic properties of clinical isolates and reference strains of M. bovis, M. bovoculi and M. ovis using a novel in vitro approach for vaccine evaluation based on two techniques, flow cytometry and western blotting (WB). Here, we demonstrated that rabbit antisera produced against reference M. bovis strain and commercial bacterin showed low number of IgG with capacity to recognize a panel of heterologous strains composed by M. bovoculi and M. ovis. On the other hand, the antisera generated against two clinical isolates of M. ovis (Mov2 and Mov3) presented high cross-reactivity levels against all M. ovis and M. bovis strains evaluated. Similarly, the antisera against Mbv3 (clinical isolate of M. bovoculi) had high levels of IgG associated on the surface of all M. bovoculi strains and most of the M. ovis strains analyzed. The WB analysis demonstrated that Moraxella spp. has multiple immunogenic antigens and most of them are shared between the three species. Based on the cross-reactivity analysis and considering the relative number of IgGs associated on the bacterial surface, we suggest that a multivalent vaccine including Mbv3, Mov2 and Mov3 strains may provide a strong and broad protection against all strains involved in IBK outbreaks.

Protein binding hot spots prediction from sequence only by a new ensemble learning method.

Hot spots are interfacial core areas of binding proteins, which have been applied as targets in drug design. Experimental methods are costly in both time and expense to locate hot spot areas. Recently, in-silicon computational methods have been widely used for hot spot prediction through sequence or structure characterization. As the structural information of proteins is not always solved, and thus hot spot identification from amino acid sequences only is more useful for real-life applications. This work proposes a new sequence-based model that combines physicochemical features with the relative accessible surface area of amino acid sequences for hot spot prediction. The model consists of 83 classifiers involving the IBk (Instance-based k means) algorithm, where instances are encoded by important properties extracted from a total of 544 properties in the AAindex1 (Amino Acid Index) database. Then top-performance classifiers are selected to form an ensemble by a majority voting technique. The ensemble classifier outperforms the state-of-the-art computational methods, yielding an F1 score of 0.80 on the benchmark binding interface database (BID) test set. AVAILABILITY: http://www2.ahu.edu.cn/pchen/web/HotspotEC.htm .

Prediction of Protein Hotspots from Whole Protein Sequences by a Random Projection Ensemble System.

Hotspot residues are important in the determination of protein-protein interactions, and they always perform specific functions in biological processes. The determination of hotspot residues is by the commonly-used method of alanine scanning mutagenesis experiments, which is always costly and time consuming. To address this issue, computational methods have been developed. Most of them are structure based, i.e., using the information of solved protein structures. However, the number of solved protein structures is extremely less than that of sequences. Moreover, almost all of the predictors identified hotspots from the interfaces of protein complexes, seldom from the whole protein sequences. Therefore, determining hotspots from whole protein sequences by sequence information alone is urgent. To address the issue of hotspot predictions from the whole sequences of proteins, we proposed an ensemble system with random projections using statistical physicochemical properties of amino acids. First, an encoding scheme involving sequence profiles of residues and physicochemical properties from the AAindex1 dataset is developed. Then, the random projection technique was adopted to project the encoding instances into a reduced space. Then, several better random projections were obtained by training an IBk classifier based on the training dataset, which were thus applied to the test dataset. The ensemble of random projection classifiers is therefore obtained. Experimental results showed that although the performance of our method is not good enough for real applications of hotspots, it is very promising in the determination of hotspot residues from whole sequences.

Automatic Estimation of Osteoporotic Fracture Cases by Using Ensemble Learning Approaches.

Ensemble learning methods are one of the most powerful tools for the pattern classification problems. In this paper, the effects of ensemble learning methods and some physical bone densitometry parameters on osteoporotic fracture detection were investigated. Six feature set models were constructed including different physical parameters and they fed into the ensemble classifiers as input features. As ensemble learning techniques, bagging, gradient boosting and random subspace (RSM) were used. Instance based learning (IBk) and random forest (RF) classifiers applied to six feature set models. The patients were classified into three groups such as osteoporosis, osteopenia and control (healthy), using ensemble classifiers. Total classification accuracy and f-measure were also used to evaluate diagnostic performance of the proposed ensemble classification system. The classification accuracy has reached to 98.85 % by the combination of model 6 (five BMD + five T-score values) using RSM-RF classifier. The findings of this paper suggest that the patients will be able to be warned before a bone fracture occurred, by just examining some physical parameters that can easily be measured without invasive operations.