Evaluation of Mastadenovirus and Rotavirus Presence in Phyllostomid, Vespertilionid, and Molossid Bats Captured in Rio Grande do Sul, Southern Brazil

Bat-borne viruses may affect public health and the global economy. These mammals have a wide geographical distribution and unique biological, physiological, and immunogenic characteristics, allowing the dissemination of many known and unknown viruses. Enteric viruses, such as adeno (AdV) and rotaviruses, are recognized as the main causative agents of disease and outbreaks. In the present study, the presence of viruses from Adenoviridae and Reoviridae families was evaluated in molossid, phyllostomid, and vespertilionid bats captured in Rio Grande do Sul, Southern Brazil, between September 2021 and July 2022. Sixty bat rectal swabs were analyzed by PCR. Eight (13.3%) samples were positive for adenovirus and classified as human mastadenovirus C (HAdV-C) (three samples) and HAdV-E (five samples) by sequencing followed by phylogenetic analysis. All samples were negative in rotavirus specific RT-PCR. This is the first study to describe the presence of HAdV in samples of Glossophaga soricina, Eptesicus brasiliensis, and Histiotus velatus. Furthermore, the presence of HAdV-E in bats was reported, which is unusual and may suggest that other HAdV genotypes, in addition to HAdV-C, may also be harbored by wild animals. The data generated in the present study reinforces the importance of eco-surveillance of viral agents related to diseases in humans and wild animals. In addition, it is essential to identify possible new hosts or reservoirs that increase the risk of spillover and dissemination of infectious pathogens, helping to prevent and control zoonotic diseases.

Characterization of avian pathogenic Escherichia coli isolates based on biofilm formation, ESBL production, virulence-associated genes, and phylogenetic groups

Escherichia coli is a part of both animal and human commensal microbiota. Avian pathogenic E. coli (APEC) is responsible for colibacillosis in poultry, an economically important disease. However, the close similarities among APEC isolates make it difficult to differentiate between pathogenic and commensal bacteria. The aim of this study was to determine phenotypic and molecular characteristics of APEC isolates and to compare them with their in vivo pathogenicity indices. A total of 198 APEC isolates were evaluated for their biofilm-producing ability and extended-spectrum β-lactamase (ESBL) production phenotypes. In addition, 36 virulence-associated genes were detected, and the isolates were classified into seven phylogenetic groups using polymerase chain reaction. The sources of the isolates were not associated with biofilms, ESBL, genes, or phylogroups. Biofilm and ESBL production were not associated with pathogenicity. Group B2 had the highest pathogenicity index. Groups B2 and E were positively associated with high-pathogenicity isolates and negatively associated with low-pathogenicity isolates. In contrast, groups A and C were positively associated with apathogenic isolates, and group B1 was positively associated with low-pathogenicity isolates. Some virulence-associated genes showed positive or negative associations with specific phylogenetic groups. None of the individual techniques produced results that correlated with the in vivo pathogenicity index. However, the combination of two techniques, namely, detection of virulence-associated genes and the phylogenetic groups, could help the classification of the isolates as pathogenic or commensal.

Avian pathogenic Escherichia coli (APEC) and uropathogenic Escherichia coli (UPEC): characterization and comparison

INTRODUCTION

Avian pathogenic E. coli (APEC) and uropathogenic E. coli (UPEC) are responsible for avian colibacillosis and human urinary tract infections, respectively. There are genetic similarities between the APEC and UPEC pathotypes, suggesting the APEC strains could be a potential reservoir of virulence and antimicrobial-resistance genes for the UPEC strains. This study aimed to characterize and compare APEC and UPEC strains regarding the phylogroup classification, pathogenicity and antimicrobial susceptibility.

METHODOLOGY

A total of 238 APEC and 184 UPEC strains were selected and characterized. The strains were assayed for antimicrobial susceptibility and classified into phylogenetic groups using a multiplex-PCR protocol. In addition, the APEC strains had previously been classified according to their in vivo pathogenicity.

RESULTS

The results showed that both pathotypes had variation in their susceptibility to most of the antimicrobial agents evaluated, with few strains classified as multidrug resistant. The highest resistance rate for both pathotypes was to amoxicillin. Classifying the APEC and UPEC strains into phylogenetic groups determined that the most frequently frequencies were for groups D and B2, respectively. These results reflect the pathogenic potential of these strains, as all the UPEC strains were isolated from unhealthy patients, and most of the APEC strains were previously classified as pathogenic.

CONCLUSIONS

The results indicate that distribution into phylogenetic groups provided, in part, similar classification to those of in vivo pathogenicity index, as it was possible to adequately differentiate most of the pathogenic and commensal or low-pathogenicity bacteria. However, no relationship could be found between the specific antimicrobial agents and pathogenicity or phylogenetic group for either pathotype.

Artificial Neural Networks on Eggs Production Data Management

Background: Eggs have acquired a greater importance as an inexpensive and high-quality protein. The Brazilian egg industry has been characterized by a constant production expansion in the last decade, increasing the number of housed animals and facilitating the spread of many diseases. In order to reduce the sanitary and financial risks, decisions regard­ing the production and the health status of the flock must be made based on objective criteria. The use of Artificial Neural Networks (ANN) is a valuable tool to reduce the subjectivity of the analysis. In this context, the aim of this study was at validating the ANNs as viable tool to be employed in the prediction and management of commercial egg production flocks.Materials, Methods & Results: Data from 42 flocks of commercial layer hens from a poultry company were selected. The data refer to the period between 2010 and 2018 and it represents a total of 600,000 layers. Six parameters were selected as “output” data (number of dead birds per week, feed consumption, number of eggs, weekly weight, weekly egg produc­tion and flock uniformity) and a total of 13 parameters were selected as “input” data (flock age, flock identification, total hens in the flock, weekly weight, flock uniformity, lineage, weekly mortality, absolute number of dead birds, eggs/hen, weekly egg production, feed consumption, flock location, creation phase). ANNs were elaborated by software programs NeuroShell Predictor and NeuroShell Classifier. The programs identified input variables for the assembly of the networks seeking the prediction of the variables called outgoing that are subsequently validated. This validation goes through the comparison between the predictions and the real data present in the database that was the basis for the work. Validation of each ANN is expressed by the specific statistical parameters multiple determination (R2) and Mean Squared Error (MSE). For instance, R2 above 0.70 expresses a good validation. ANN developed for the output variable “number of dead birds per week” presented R2= 0.9533 and MSE= 256.88. For “feed consumption”, the results were R2= 0.7382 and MSE= 274.56. For “number of eggs (eggs/hen)”, the results were R2= 0.9901 and MSE= 172.26. For “weekly weight”, R2= 0.9712 and MSE= 11154.41. For “weekly egg production”, R2= 0.8015 and MSE= 72.60. For “flock uniformity”, R2= -2.9955 and MSE= 431.82.Discussion: From the six ANN designed in this study, in five it was possible to validate the predictions by comparing predictions with the real data. In one output parameter (“flock uniformity”), it was not possible to have adequate validation due to insufficient data in our database. For “number of dead birds per week”, “feed consumption”, “weekly weight” and “uniformity”, the most important variable was “flock age” (27.5%, 52.5%, 55.2% and 37.9%, respectively). For “number of eggs (eggs/hen)”, “uniformity” (52.1%) was the most relevant variable for prediction. For “weekly egg production”, “flock age” and “number of eggs (eggs/hen)” were the most important zootechnical parameters, both with a relative contribution of 38.2%. The results showed that even with the use of a robust tool such as ANNs, it is necessary to have well-noted and clear information that expresses the reality of the flocks. In any case, the results presented allow us to state that ANNs are capable for the management of data generated in a commercial egg production facility. The process of evaluation of these data would be improved if ANNs were routinely used by the professionals linked to this activity.

Classification of Avian Pathogenic Escherichia coli (APEC) and Human Uropathogenic Escherichia coli (UPEC) in Phylogenetic Groups and Association with Pathogenicity In Vivo

Background: Avian pathogenic E. coli (APEC) and uropathogenic E. coli (UPEC) are responsible, respectively, for avian colibacillosis and for 80% of urinary tract infections in humans. E. coli control is difficult due to the absence of a reliable method to differentiate pathogenic and commensal strains. Genetic similarity between APEC and UPEC suggests a common ancestral origin and the capability of potentially pathogenic strains to affect human health. The classification in phylogenetic groups facilitates the identification of pathogenic strains. The objective of this work was to classify APEC and UPEC E. coli strains into phylogenetic groups and to associate it with in vivo pathogenicity.Materials, Methods & Results: 460 APEC and 450 UPEC strains, stored in BHI with glycerol at -80°C, were selected. APEC strains were isolated from cellulitis, respiratory tract and poultry litter of broiler flocks from Southern Brazil. The UPEC strains from urinary tract infection were provided by a hospital in Porto Alegre. After DNA extraction, APEC and UPEC strains were classified into four phylogenetic groups (A, B1, B2 and D) by a multiplex-PCR protocol for the detection of the chuA and yjaA genes and the TspE4.C2 DNA fragment. Phylogenetic groups were associated with pathogenicity indexes (PI), presented on a scale of 0 to 10, which were previously obtained through the inoculation of APEC strains in one-day-old chicks. Phylogenetic groups were also associated with the presence of 38 virulence-associated genes. The multiplex-PCR protocol was able to differentiate 100% of the APEC and UPEC strains in the four phylogenetic groups. The majority of APEC strains were classified into phylogenetic groups D (31.1%) and B2 (24.1%). On the other hand, the majority of UPEC strains were classified into B2 (53.6%). Among APEC strains, five genes (crl, mat, ompA, fimC and fimH) were detected in more than 80% of strains in all groups. Some genes showed a significant association with specific phylogenetic groups. Gene ireA was exclusively to group D, kpsMT II and cvaC to B2 and sat was exclusively to B1. Four genes (ireA, sfa/focCD, ibeA, tsh) were detected in more than 70% of UPEC strains in all phylogenetic groups. Gene iroN1 showed a significant association exclusively to group A, and iucD, papC and irp2 to B1 group. APEC isolated from poultry litter presented significantly lower PIs than those isolated from cellulitis and from birds with respiratory signs. The average PI from B2 group was significantly higher than that of D group. In addition, the PIs of the two groups were significantly higher than those of A and B1.Discussion: The high frequency of UPEC classified as B2 is in agreement with the literature. More virulent strains are usually classified into B2 group and some of them may be classified into D group. On the other hand, the distribution of APEC isolates in phylogenetic groups is characterized by variability and it is usually related to the origin of the isolates, as observed in the study. Since E. coli strains isolated from human and poultry face similar challenges in infection establishment of extraintestinal sites, they may share some virulence genes. In this study, most of the 38 genes presented a high frequency in both APEC and UPEC strains. As the distribution of APEC strains in phylogenetic groups showed a significant association with pathogenicity, multiplex-PCR becomes an important tool for screening the pathogenicity of strains isolated from the poultry production chain.