Evidence of Mycoplasma spp. Transmission by Migratory Wild Geese

Mycoplasma infections have been found in different species of waterfowl worldwide. However, the question of how the pathogens have been transmitted and dispersed is still poorly understood. Samples collected from clinically healthy greater white-fronted geese (Anser albifrons) (N = 12), graylag geese (Anser anser) (N = 6), taiga bean geese (Anser fabalis) (N = 10), and barnacle geese (Branta leucopsis) (N = 1) were tested for Mycoplasma spp. All Mycoplasma-positive samples were specified by species-specific PCR for Mycoplasma anserisalpingitidis (formerly known as Mycoplasma sp. 1220), M. anseris, M. anatis, and M. cloacale. The presence of Mycoplasma spp. was confirmed in 22 of 29 sampled birds (75.9%). Mycoplasma anserisalpingitidis was the most frequently detected species (15 of 22, 68.2%). However, we did not detect any of the other Mycoplasma spp. typical for geese, among which are M. anatis, M. anseris, and M. cloacale. Phylogenetic analysis revealed that Polish sequences of M. anserisalpingitidis formed a distinct branch, along with 2 Hungarian isolates obtained from domestic geese. Eight of the samples identified as Mycoplasma spp.-positive were negative for the aforementioned Mycoplasma species. A phylogenetic tree constructed based on partial 16S rRNA gene analysis showed that Mycoplasma spp. sequences collected from Polish wild geese represent a distinct phylogenetic group with Mycoplasma sp. strain 2445 isolated from a domestic goose from Austria. The results of our study showed that wild geese could be a reservoir and vector of different species of the Mycoplasma genus that can cause significant economic losses in the domestic goose industry

Reflected Light Spectrometry and AI-Based Data Analysis for Detection of Rapid Chicken Eggshell Change Caused by Mycoplasma Synoviae

Mycoplasma synoviae (MS) is a pathogen that causes economic losses in the poultry industry. It can be transmitted, amongst others, via the respiratory tract and spread relatively quickly. As such, MS infections are mainly controlled by maintaining MS-free breeder flocks. Routine diagnosis for the detection of MS may be based on serological, culture, and molecular tests. Here, we propose an optical solution where AI-based analysis of spectral data obtained from the light reflected from the eggshells is used to determine whether they originate from healthy or Mycoplasma synoviae-infected hens. The wavelengths proposed for spectral MS detection are limited to those of VIS and NIR DPSS lasers, which are freely accessible on market. The results are satisfactory: for white eggshells, the F-score is over 95% for five different combinations of wavelengths (using eight or nine wavelengths); for brown eggshells, the F-score is above 85%, also for five different combinations of 6–9 wavelengths

Occurrence of Mycoplasma gallisepticum in wild birds: A systematic review and meta-analysis.

Mycoplasma gallisepticum is one of the most important poultry pathogens that can also infect wild birds, but knowledge of potential non-poultry hosts that could be reservoirs of M. gallisepticum is limited. For the paper presented here, we screened three databases (PubMed, Scopus, and the Web of Knowledge) to find articles on the occurrence of M. gallisepticum in different wild bird species that were published between 1951 and 2018. Among 314 studies found, we selected and included 50 original articles that met the pre-established criteria. From those publications we extracted the following information: name of the first author, year of publication, year of sample isolation, country, region, number of birds sampled, number of birds tested by each method, number of positive samples, diagnostic criteria, and if birds were wild or captive. Because different detection techniques were used to confirm the presence of M. gallisepticum in one animal, we decided to perform the meta analyses separately for each method. The estimated prevalence of M. gallisepticum in wild birds was different by each method of detection. Our summary revealed that M. gallisepticum was present in 56 species of bird belonging to 11 different orders, of which 21 species were reported suffering both past and current infection. Our work provides information on wild bird species that could be considered potential reservoirs or carriers of M. gallisepticum and could be helpful to set the direction for future research on the spread and phylogeny of M. gallisepticum in different hosts

Molecular Detection and Phylogenetic Analysis of Riemerella anatipestifer in Poultry and Wild Geese in Poland

Riemerella anatipestifer (RA) is one of the most relevant bacterial pathogens of commercial waterfowl from clinical and economic points of view. Our study aimed to evaluate the prevalence of RA infection in different types of commercial poultry in Poland and verify the potential role of wild geese as vectors of this pathogen. We tested a total of 126 poultry flocks, including geese (N = 20), ducks (N = 42), turkeys (N = 64) and 19 wild geese, including greater white-fronted geese (N = 9), greylag geese (N = 5) and Taiga bean geese (N = 5). Tracheal swabs were examined for RA using a PCR targeting a conserved region of the 16S rRNA gene. Selected PCR products were sequenced to perform the phylogenetic analysis. Among the commercial poultry, the highest RA prevalence was found in flocks of ducks (35.7%) and geese (30.0%), whereas the lowest one was found in turkeys (3.2%). Most tested wild geese (94.7%) were RA positive. The phylogenetic analysis showed relatively low genetic diversity of the sequences analyzed, which gathered in two clusters of the phylogenetic tree, and the minimum nucleotide identity was 98.6%. Our results would support the contention that RA isolates from commercial poultry circulate in wild bird populations but are not transmitted back to poultry

The Microbial Community of the Respiratory Tract of Commercial Chickens and Turkeys

Respiratory tract health critically affects the performance of commercial poultry. This report presents data on the microbial community in these organs from a comprehensive study of laying chickens and turkey breeders. The main objective was to characterize and compare the compositions of the respiratory system bacteria isolated from birds of different ages and geographical locations in Poland. Using samples from 28 turkey and 26 chicken flocks, the microbial community was determined by 16S ribosomal RNA sequencing. There was great variability between flocks. The diversity and abundance of upper respiratory tract (URT) bacteria was greater in chickens than in turkeys. At the phyla level, the URT of the chickens was heavily colonized by Proteobacteria, which represented 66.4% of the total microbiota, while in turkeys, this phylum constituted 42.6% of all bacteria. Firmicutes bacteria were more abundant in turkeys (43.2%) than in chickens (24.1%). The comparison of the respiratory tracts at the family and genus levels showed the diversity and abundance of amplicon sequence variants (ASV) differing markedly between the species. Potentially pathogenic bacteria ASV were identified in the respiratory tract, which are not always associated with clinical signs, but may affect bird productivity and performance. The data obtained, including characterization of the bacterial composition found in the respiratory system, may be useful for developing effective interventions strategies to improve production performance and prevent and control disease in commercial laying chickens and turkeys

Multispectral Portable Fibre-Optic Reflectometer for the Classification of the Origin of Chicken Eggshells in the Case of Mycoplasma synoviae Infections

The proper classification of the origins of food products is a crucial issue all over the world nowadays. In this paper, the authors present a device—a multispectral portable fibre-optic reflectometer and signal processing patch—together with a machine-learning algorithm for the classification of the origins of chicken eggshells in the case of Mycoplasma synoviae infection. The sensor device was developed based on previous studies with a continuous spectrum in transmittance and selected spectral lines in reflectance. In the described case, the sensor is based on the integration of reflected spectral data from short spectral bands from the VIS and NIR region, which are produced by single-colour LEDs and introduced to the sample via a fibre bundle. The measurement is carried out in a sequence, and the reflected signal is pre-processed to be put in the machine learning algorithm. The support vector machine algorithm is used together with three different types of data normalization. The obtained results of the F-score factor for classification of the origins of samples show that the percentages of eggs coming from Mycoplasma synoviae infected hens are up to 87% for white and 96% for brown eggshells