Background and Aim: Drinking water of poor microbiological quality contains high percentages of microbes causing outbreaks of mainly coliform-related diseases. These microbes could be controlled by many hygienic standards including disinfection, but disinfectants misuse causes the developing of disinfectant-resistant strains. The present study aimed to investigate drinking water bacterial profile, determine chlorine-resistant strains, and statistically correlate that with the used disinfectant and disinfection process variables. In vitro evaluation of the bactericidal effect of the most commonly used disinfectants in cattle operations against the isolated chlorine-resistant strains and detection of qacE resistance gene in the isolated chlorine-resistant Escherichia coli strains in some cattle farms suffering coliform and non-coliform related disease around Egypt.Materials and Methods: A structured questionnaire is used to survey a convenience sample of 132 Egyptian cattle beef and dairy farms suffering emerged epidemics to identify commonly used disinfection process, disinfectant types, disinfectants frequency, and rate of use. One hundred and thirty-two water samples were collected for microbiological analysis to obtain water bacterial profile and testing resistance to chlorine. Statistical analysis was performed to identify the level of association between microbial profile and presence of chlorine-resistant strains in each farm with used disinfection, disinfectant types, and rate of use in these farms.
Results: A wide range of disinfectant types used for variable purposes inside cattle farms with a different frequency of use and the highest percent of farms 25.8% use 4-5 types of disinfectants, followed by 25% of farms use two types, then 18.9% use three types. Microbial profile of water samples revealed isolation of E. coli, Streptococcus faecalis, Pseudomonas aeruginosa, Klebsiella spp., Proteus spp., Salmonella spp., Enterobacter spp., Citrobacter spp., Shigella flexneri, Serratia marcescens, and Yersinia enterocolitica in percent (98.5, 97.7, 97.7, 76.5, 66.7, 36.4, 78.8, 74.2, 30.3, 29.5, and 14.4% of cattle farms, respectively), from which five E. coli, four Salmonella, four Pseudomonas, two Klebsiella, and four Streptococcus strains expressed chlorine resistance. Statistical analysis showed weak to moderate correlation (rho 0.15-0.46) between bacterial profile strains count and presence of resistant strains with different farm disinfection, disinfectant types, and rate of use. Experimental evaluation of the bactericidal effect of the eight selected disinfectants on the chlorine-resistant isolated strains revealed that peroxymonosulfate killed 19/19 isolated strains/15 min contact time, and quaternary ammonium compounds killed only 3/19 strains/15 min contact time. The qacE resistance gene was detected in 3/4 isolated chlorine-resistant E. coli strains.
Conclusion: Drinking water microbial profile strains and resistance to disinfectants are widely varied in cattle farms, and this variance depends on critical factors among which the disinfection process types used disinfectant types and frequency of disinfectants use or change.

A serious global public health emergency emerged late November 2019 in Wuhan City, China, by a new highly pathogenic virus, SARS-CoV-2. The virus evolution spread has been tracked by three developing databases: GISAID, Nextstrain and PANGO to understand its circulating variants. In this study, 110 diagnosed positive COVID-19 patient's samples, were collected from Kasr Al-Aini Hospital and the Children Cancer Hospital Egypt 57357 between May 2020 and January 2021, with clinical severity ranging from mild to severe. The viral genomes were sequenced by next generation sequencing, and phylogenetic analysis was performed to understand viral transmission dynamics. According to Nextstrain clades, most of our sequenced samples belonged to clades 20A and 20D, which in addition to clade 20B were present from the beginning of sample collection in May 2020. Clades 19A and 19B, on the other hand, appeared in the mid and late 2020 respectively, followed by the disappearance of clade 20B at the end of 2020. We identified a relatively high prevalence of the D614G spike protein variant and novel patterns of mutations associated together and with different clades. We also identified four mutations, spike H49Y, ORF3a H78Y, ORF8 E64stop and nucleocapsid E378V, associated with higher disease severity. Altogether, our study contributes genetic, phylogenetic, and clinical correlation data about the spread of the SARS-CoV-2 pandemic in Egypt.

The overall pattern of the SARS-CoV-2 pandemic so far has been a series of waves; surges in new cases followed by declines. The appearance of novel mutations and variants underlie the rises in infections, making surveillance of SARS-CoV-2 mutations and prediction of variant evolution of utmost importance. In this study, we sequenced 320 SARS-CoV-2 viral genomes isolated from patients from the outpatient COVID-19 clinic in the Children's Cancer Hospital Egypt 57357 (CCHE 57357) and the Egypt Center for Research and Regenerative Medicine (ECRRM). The samples were collected between March and December 2021, covering the third and fourth waves of the pandemic. The third wave was found to be dominated by Nextclade 20D in our samples, with a small number of alpha variants. The delta variant was found to dominate the fourth wave samples, with the appearance of omicron variants late in 2021. Phylogenetic analysis reveals that the omicron variants are closest genetically to early pandemic variants. Mutation analysis shows SNPs, stop codon mutation gain, and deletion/insertion mutations, with distinct patterns of mutations governed by Nextclade or WHO variant. Finally, we observed a large number of highly correlated mutations, and some negatively correlated mutations, and identified a general inclination toward mutations that lead to enhanced thermodynamic stability of the spike protein. Overall, this study contributes genetic and phylogenetic data, as well as provides insights into SARS-CoV-2 viral evolution that may eventually help in the prediction of evolving mutations for better vaccine development and drug targets.