Development and validation of multiplex PCR based molecular serotyping of Salmonella serovars associated with poultry in India.

Salmonella species are Gram-negative bacteria with more than 2600 serovars. Among these serovars, many are associated with various diseases in livestock and humans. White Kauffman Le-Minor (WKL) serotyping scheme applies specific serum to determine the serovars of Salmonella. Recent studies have applied molecular methods for serovar predictions. These methods include PCR, hybridization and sequence data to detect/predict serovar-specific genetic elements. Among these, PCR is a robust method if the unique genetic element is already known. Within this context, also involving novel primers, two multiplex PCR assays were standardized to detect six important Salmonella serovars viz. Typhimurium, Enteritidis, Kentucky, Infantis, Virchow and Gallinarum associated with poultry in India. The developed PCR assays showed targeted serovar specificity. Serial dilution experiments of both kit-based and crude lysate DNA preparations indicated similar applicability of both methods for testing from pure cultures. Further the developed assays were validated with 25 recent field isolates to confirm the applicability in routine diagnosis. The PCR assay could predict all the targeted serovars (17/25) with 100% specificity (CI-95%; 0.63-1). Molecular serotyping can reduce the number of serum used in comparison to the conventional serotyping which involves more random application of serum.

Pathotyping and antimicrobial susceptibility testing of Escherichia coli isolates from neonatal calves.

Neonatal calf mortality is a major concern to livestock sector worldwide. Neonatal calf diarrhoea (NCD), an acute severe condition causes morbidity and mortality in calves. Amongst various pathogens involved in NCD, E. coli is considered as one of the major causes. The study was targeted to characterize E. coli isolates from neonatal calves for diarrhoeagenic Escherichia coli (DEC) types (pathotyping), antimicrobial resistance (AMR) profiling and to correlate with epidemiological parameters. From neonates, a total of 113 faecal samples were collected, out of that 308, lactose fermenting colonies were confirmed as E. coli. Pathotypable isolates (12.3%) were represented by STEC (6.1%), EPEC (2.9%), ETEC (1.9%), EAEC (0.9%) and EHEC (0.3%). Occurrence of STEC was more in non-diarrhoeic calves, whereas ETEC was observed more in diarrhoeic calves. EPEC occurrence was observed in both diarrhoeic and non-diarrhoeic calves. Fishers extract test showed no significant association for occurrence of DEC types to type of dairies, health status, species, breed, age and sex of neonatal calves. Two hundred and eighty isolates were tested for antimicrobial susceptibility. The isolates showed maximum resistance towards ampicillin (55.4%) followed by tetracycline (54.3%), while minimum resistance was observed towards meropenem (2.5%). Multidrug resistant E. coli isolates were found to be 139 (49.6%), and Extended-spectrum beta-lactamase (ESBL) producers were 120 (42.9%). DEC pathotypes like STEC, ETEC, EHEC and EAEC that are also multidrug resistant present in neonatal calves have zoonotic potential and hence are of public health significance.

Analysis of bluetongue disease epizootics in sheep of Andhra Pradesh, India using spatial and temporal autocorrelation.

Bluetongue (BT) disease poses a constant risk to the livestock population around the world. A better understanding of the risk factors will enable a more accurate prediction of the place and time of high-risk events. Mapping the disease epizootics over a period in a particular geographic area will identify the spatial distribution of disease occurrence. A Geographical Information System (GIS) based methodology to analyze the relationship between bluetongue epizootics and spatial-temporal patterns was used for the years 2000 to 2015 in sheep of Andhra Pradesh, India. Autocorrelation (ACF), partial autocorrelation (PACF), and cross-correlation (CCF) analyses were carried out to find the self-dependency between BT epizootics and their dependencies on environmental factors and livestock population. The association with climatic or remote sensing variables at different months lag, including wind speed, temperature, rainfall, relative humidity, normalized difference vegetation index (NDVI), normalized difference water index (NDWI), land surface temperature (LST), was also examined. The ACF & PACF of BT epizootics with its lag showed a significant positive autocorrelation with a month's lag (r = 0.41). Cross-correlations between the environmental variables and BT epizootics indicated the significant positive correlations at 0, 1, and 2 month's lag of rainfall, relative humidity, normalized difference water index (NDWI), and normalized difference vegetation index (NDVI). Spatial autocorrelation analysis estimated the univariate global Moran's I value of 0.21. Meanwhile, the local Moran's I value for the year 2000 (r = 0.32) showed a high degree of spatial autocorrelation. The spatial autocorrelation analysis revealed that the BT epizootics in sheep are having considerable spatial association among the outbreaks in nearby districts, and have to be taken care of while making any forecasting or disease prediction with other risk factors.