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Fecal microbiota transplantation (FMT) has been shown to improve gut dysbiosis in dogs; however, it has not completely been understood in police dogs. This study aimed to investigate the effects of FMT on performance and gut microflora in Kunming police dogs. Twenty Wolf Cyan dogs were randomly assigned to receive physiological saline or fecal suspension at low, medium, or high doses through oral gavage for 14 days. Growth performance, police performance, serum biochemical profiling, and gut microflora were determined 2-week post-FMT. Dogs after FMT treatment were also subjected to an hour road transportation and then were evaluated for serum stress indicators. Overall, FMT enhanced the growth performance and alleviated diarrhea rate in Kunming dogs with the greatest effects occurring in the low dose FMT (KML) group. The improvement of FMT on police performance was also determined. These above alterations were accompanied by changed serum biochemical parameters as indicated by elevated total protein and albumin and reduced total cholesterol and glycerol. Furthermore, the serum stress indicators after road transportation in dog post-FMT significantly decreased. Increased bacterial diversity and modified bacterial composition were found in the feces of dogs receiving FMT. The fecal samples from FMT dogs were characterized by higher abundances of the genera Lactobacillus, Prevotella, and Fusobacterium and lower concentrations of Cetobacterium, Allobaculum, Bifidobacterium, and Streptococcus. The present study supports a potential benefit of FMT on police performance in Kunming dogs. Key points: • FMT improves the growth performance and reduces diarrhea rates in Kunming police dogs. • FMT alleviates the serum stress profiles after road transportation in Kunming police dogs. • FMT modifies the gut microbiota composition of Kunming police dogs. [ABSTRACT FROM AUTHOR]

Water contamination with faecal matter is usually the main cause of microbial waterborne diseases. Such diseases are an alarming situation for small cities in developing countries like India. In this research, to check the microbiological status of drinking water in Solan, Himachal Pradesh (India), water samples were collected from baories/stepwells (n = 14), handpumps (n = 9), and the municipal water distribution system (MWDS) (n = 2) in alternative months of the year (covering three main seasons). In 6 months, 150 samples were collected, and they were all examined for the presence of total coliforms and other bacterial pathogens. The associations between the isolates' ecological and seasonal prevalence were also examined. The coliforms were detected by the Most Probable Number (MPN) method, whose range was noticed from the 2–540/100-ml MPN index. The colony forming unit (CFU) count for different samples at the base log 10 value ranged from 3.03 to 6.19. Different genera isolated and identified were Escherichia coli, Salmonella enteric subsp. enterica, Pseudomonas spp., Klebsiella spp., and Staphylococcus aureus. Overall, 74% of the isolates identified in water samples were from the Enterobacteriaceae family. E. coli was about 42.67% (n = 102), followed by Salmonella enterica subsp. enterica 20.92% (n = 50), Staphylococcus aureus 13.38% (n = 32), Pseudomonas spp. 12.55% (n = 30), and Klebsiella spp. 10.46% (n = 25) amongst the total of 239 isolates. The seasonal impact and the dependency of the occurrence of bacteria on one another were determined to be insignificant in the Spearman correlation test. These results showed that external factors (anthropogenic activities) are mainly responsible for the presence of these bacteria in water resources. The occurrence of bacterial isolates has been noticed in all water samples, irrespective of collecting site or season. [ABSTRACT FROM AUTHOR]

Coastal water quality is an important parameter that directly influences human health (bathing and shellfish consumption). In this study, we assessed the surface water quality of three stations in Bou-Ismail Bay (central Algerian) to determine its potential impact on marine aquaculture. During the study period, a significant difference was recorded for salinity (30.35 − 36.06 psu) and suspended particulate matter (SPM) (35.04 − 73.53 mg/l). Ammonium ranged from 0.88 to 76.66 μM. Nitrite and nitrate varied from 0.08 to 2.6 μM and 0.29 to 7.58 μM, respectively, while phosphate varied from 0.11 to 2.31 μM. The enumeration of fecal coliform (FC) and enterococci (ENT) showed that S1 station is the most contaminated. PCA of the datasets highlighted the generation of two groups of sampling stations: the first group underlines S2 and S3 stations characterized by a low level of pollution independent of temporal variations. The second group presented S1 station was highly polluted and indiscriminately fluctuated over time. Our findings showed that more intensive water quality monitoring programs should be particularly addressed in shellfish areas. [ABSTRACT FROM AUTHOR]

Animal diet and health influence fitness, making individual variation in these markers essential for understanding how individuals and populations respond to their environments. Faecal and hair samples provide a record of this information and can be non-invasively collected from animals in the field. However, physiology, diet, and susceptibility to parasitic infections vary within individuals, requiring repeated samples from individuals. We developed a technique using biotelemetry data for individual identification of non-invasive faecal material and hair sampled from female elk (Cervus canadensis). We non-invasively collected individually genotyped faecal and hair samples from resting sites, then compared the accuracy of supervised machine learning models to predict the individual identities of the samples. We found both the tightness of global positioning system point clusters and activity level surrounding the sample allowed us to positively identify samples belonging to specific individuals with 77% accuracy. Our approach can be applied to other populations for which biotelemetry data are available and is potentially adaptable for other species. Furthermore, application of our approach will reduce the need for individual identification of non-invasive samples using genetic analysis, which is costly and prone to low recovery success. Increased access to physiological, dietary, and health information obtainable from individual non-invasive samples will strengthen our understanding of animal responses to their environments. [ABSTRACT FROM AUTHOR]

Food safety and foodborne diseases are significant global public health concerns. Meat and poultry carcasses can be contaminated by pathogens like E. coli and salmonella, by contact with animal fecal matter and ingesta during slaughter and processing. Since fecal matter and ingesta can host these pathogens, detection, and excision of contaminated regions on meat surfaces is crucial. Fluorescence imaging has proven its potential for the detection of fecal residue but requires expertise to interpret. In order to be used by meat cutters without special training, automated detection is needed. This study used fluorescence imaging and deep learning algorithms to automatically detect and segment areas of fecal matter in carcass images using EfficientNet-B0 to determine which meat surface images showed fecal contamination and then U-Net to precisely segment the areas of contamination. The EfficientNet-B0 model achieved a 97.32% accuracy (precision 97.66%, recall 97.06%, specificity 97.59%, F-score 97.35%) for discriminating clean and contaminated areas on carcasses. U-Net segmented areas with fecal residue with an intersection over union (IoU) score of 89.34% (precision 92.95%, recall 95.84%, specificity 99.79%, F-score 94.37%, and AUC 99.54%). These results demonstrate that the combination of deep learning and fluorescence imaging techniques can improve food safety assurance by allowing the industry to use CSI-D fluorescence imaging to train employees in trimming carcasses as part of their Hazard Analysis Critical Control Point zero-tolerance plan. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease COVID-19 has infected over 46 million people in 219 countries and territories. Following evidence of viral loadings and infectivity of feces of infected individuals, public health authorities have suggested to take precautions on the transmission of COVID-19 via fecal-associated routes. Recent discussions on fecal transmission of COVID-19 have mainly focused on municipal sewage. Yet, a widely neglected aspect in containing the virus is that a major part of the population in developing regions do not have access to private, clean sanitary facilities. Therefore, we hypothesize that open defecation and the prevalent use of squat toilets are additional risk factors in those communities. Here, we review fecal transmission of COVID-19, the practices of open defecation, and the resultant routes of transmission of fecal pathogens. Also, we highlight the open design of common squat toilets and the potential exposure to fecal droplets and residues. We observed that at least 20 countries reporting more than 10,000 confirmed infections have 5–26% of their population practicing open defecation. We illustrate the potential routes of transmission of COVID-19 and other fecal pathogens via human feces in communities practicing open defecation. Here, poor hand hygiene, contaminated shoes and objects, mechanical vectors, and outdoor human activities can all contribute to fecal transmission. Other risk factors include squat pans with lidless designs and open flushing mechanisms, in-cubicle open waste bins, and the lack of water-sealing U-traps in squat toilets. [ABSTRACT FROM AUTHOR]

A dog-associated 16S rDNA genetic marker (ED-1) was designed to detect dog fecal contamination in water through a comparative bioinformatics analysis of Faecalibacterium sequences. For the dog fecal samples, ED-1 had 100% specificity, a high positive rate (89% in dog feces and 92.3% in dog fecal–contaminated water samples), and a low detection limit (107 copies/100 mL) in dog-contaminated water samples. Detection of water samples from seven provinces or cities of China showed that ED-1 was stable enough to be applied in practice. Furthermore, the abundance and diversity of dog gut microbiota from two private house pets (PHP) and Third Military Medical University (TMMU) dogs were estimated by using operational taxonomic units, and the significant differences of dog feces were found, as the PHP dogs have a more diverse diet and closer contact with human than dogs in TMMU. However, ED-1 could detect the feces from the two regions, indicating that ED-1 has good reliability. [ABSTRACT FROM AUTHOR]

A traditional method of enumerating Clostridium perfringens using membrane filtration (MF) as an indicator of fecal contamination was compared to recently developed rapid method using Rapid Fung Double Tube (RFDT) in an evaluation to characterize the extent of sewage contamination in sediments of the Great Lakes. Evaluation of these two methods included determining C. perfringens concentrations and recovery efficiencies from sewage, sewage-spiked sediments, and water (surface and bottom) and sediment samples collected from two Great Lakes. The RFDT method proved to be a superior method for identifying C. perfringens in lake sediments compared to MF, as it had higher recovery efficiency and was more rapid, reliable, simple, and effective. This study provides biological evidence of the long-term deposition and movement of sewage particulates in the Great Lakes environment and demonstrates the potential usefulness of C. perfringens as a tracer for sewage contamination using a reliable enumeration method. [ABSTRACT FROM AUTHOR]

Bacteroides- Prevotella group is one of the most promising targets for detecting fecal contamination in water environments, principally due to its host-specific distributions and high concentrations in feces of warm-blooded animals. We developed real-time PCR assays for quantifying chicken/duck-, chicken-, and duck-associated Bacteroides- Prevotella 16S rRNA genetic markers (Chicken/Duck-Bac, Chicken-Bac, and Duck-Bac). A reference collection of DNA extracts from 143 individual fecal samples and wastewater treatment plant influent was tested by the newly established markers. The quantification limits of Chicken/Duck-Bac, Chicken-Bac, and Duck-Bac markers in environmental water were 54, 57, and 12 copies/reaction, respectively. It was possible to detect possible fecal contaminations from wild ducks in environmental water with the constructed genetic marker assays, even though the density of total coliforms in the identical water samples was below the detection limit. Chicken/Duck-Bac marker was amplified from feces of wild duck and chicken with the positive ratio of 96 and 61 %, respectively, and no cross-reaction was observed for the other animal feces. Chicken-Bac marker was detected from 70 % of chicken feces, while detected from 39 % of cow feces, 8.3 % of pig feces, and 12 % of swan feces. Duck-Bac marker was detected from 85 % of wild duck feces and cross-reacted with 31 % of cow feces. These levels of detection specificity are common in avian-associated genetic markers previously proposed, which implies that there is a practical limitation in the independent application of avian-associated Bacteroides- Prevotella 16S rRNA genetic markers and a combination with other fecal contamination markers is preferable for detecting fecal contamination in water environments. [ABSTRACT FROM AUTHOR]

Molecular methods are useful both to monitor natural communities of bacteria, and to track specific bacterial markers in complex environments. Length-heterogeneity polymerase chain reaction (LH-PCR) and terminal restriction fragment length polymorphism (T-RFLP) of 16S rDNAs discriminate among 16S rRNA genes based on length polymorphisms of their PCR products. With these methods, we developed an alternative indicator that distinguishes the source of fecal pollution in water. We amplify 16S rRNA gene fragments from the fecal anaerobic genus Bacteroides with specific primers. Because Bacteroides normally resides in gut habitats, its presence in water indicates fecal pollution. Molecular detection circumvents the complexities of growing anaerobic bacteria. We identified Bacteroides LH-PCR and T-RFLP ribosomal DNA markers unique to either ruminant or human feces. The same unique fecal markers were recovered from polluted natural waters. We cloned and sequenced the unique markers; marker sequences were used to design specific PCR primers that reliably distinguish human from ruminant sources of fecal contamination. Primers for more species are under development. This approach is more sensitive than fecal coliform assays, is comparable in complexity to standard food safety and public health diagnostic tests, and lends itself to automation and high-throughput. Thus molecular genetic markers for fecal anaerobic bacteria hold promise for monitoring bacterial pollution and water quality. [ABSTRACT FROM AUTHOR]