Prevalence and Antimicrobial Resistance Patterns of &amp;lt;i&amp;gt;Shigella&amp;lt;/i&amp;gt; in Ethiopia from 2000 to 2018: A Critical Review

Teferi, Samuel Chane

doi:10.11648/j.cbe.20200502.12

Cited by 2 publications

(2 citation statements)

References 15 publications

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“…STEC and Shigella were most prominent in stool and were resistant to Meropenem (30%), Azactum (30%), Tetracycline (30%), Ceftazidime (60%), and Levofloxacin (60%). Amoxicillin, Ampicillin, Chloramphenicol, and Tetracycline were found noticeably ineffective against clinically isolated Shigella by Teferi (2020) [19]. Jain et al (2021) described STEC as exhibiting significant resistance against Amoxicillin (98%), Cefuroxime (75%), and Cotrimoxazole (62%) [20].…”

Section: Discussionmentioning

confidence: 99%

Isolation, Identification and Antibiotic Resistance of Different Clinical Isolates in Savar Area, Bangladesh

Fayez Ahmed,

Najmun Nahar,

Tanvir Ahmed

et al. 2023

biosight

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Introduction: The rise of multidrug-resistant (MDR) microorganisms, which pose a grave threat, has made choosing antibiotics to treat bacterial infections incredibly challenging. The prescription antibiotics have to consistently be effective against the identified related infections. Thus the research team wanted to find the antibiotic sensitivity profiles and pathogenic bacterial isolates in various patient specimens. Methods: The collection of 403 clinical samples of throat swabs, sputum, blood, stool, and urine from people of both genders and various ages was performed aseptically. Identification was carried out by microscopic, cultural, biochemical, and serological analysis. Finally, the disk diffusion method by Kirby-Bauer was employed to determine antibiotic responsiveness profiling. Results: A total of 93 samples (23.08%) were identified as positive isolates comprising 28.74% (25/87) of urine culture, followed by 24.32% (27/111) of blood, 23.08% (15/65) of stool, 20% (07/35) of throat swabs, and 18.1% (19/105) of sputum culture. Gram-negative bacteria 81(87.1%) showed more prevalence than Gram-positive bacteria 12 (12.90%). The most frequently identified isolates were Klebsiella spp. (24%), Salmonella spp. (23%), E. coli (17%), Pseudomonas spp. (5%), and Enterococcus spp. (3%). The infections showed more prevalence within the age group of 16-46 years (60.2%) and among males (48%) than females (46%). Conclusions: It was found that E. coli was the most abundant bacteria isolated from urine, Klebsiella spp. was the most abundant bacteria isolated from sputum and throat swabs, and Shiga toxin-producing Escherichia coli was the most abundant bacteria isolated from stool. Amikacin, Ciprofloxacin, Gentamicin, Imipenem, and Levofloxacin were considerably effective antibiotics, whereas Cefotaxime, Ceftazidime, Cefuroxime, Mecillinam, and Meropenem were least effective.

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Section: Discussionmentioning

confidence: 99%

Isolation, Identification and Antibiotic Resistance of Different Clinical Isolates in Savar Area, Bangladesh

Fayez Ahmed,

Najmun Nahar,

Tanvir Ahmed

et al. 2023

biosight

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“…Nevertheless, most of the cases remain unreported in these regions. It is expected that if no action is taken, this number is expected to increase to 4.2 million in Africa and 10 million worldwide by 2050 [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

An integrated in-silico approach for drug target identification in human pathogen Shigella dysenteriae

Qureshi,

Basheer,

Sajjad

et al. 2024

PLoS ONE

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Shigella dysenteriae, is a Gram-negative bacterium that emerged as the second most significant cause of bacillary dysentery. Antibiotic treatment is vital in lowering Shigella infection rates, yet the growing global resistance to broad-spectrum antibiotics poses a significant challenge. The persistent multidrug resistance of S. dysenteriae complicates its management and control. Hence, there is an urgent requirement to discover novel therapeutic targets and potent medications to prevent and treat this disease. Therefore, the integration of bioinformatics methods such as subtractive and comparative analysis provides a pathway to compute the pan-genome of S. dysenteriae. In our study, we analysed a dataset comprising 27 whole genomes. The S. dysenteriae strain SD197 was used as the reference for determining the core genome. Initially, our focus was directed towards the identification of the proteome of the core genome. Moreover, several filters were applied to the core genome, including assessments for non-host homology, protein essentiality, and virulence, in order to prioritize potential drug targets. Among these targets were Integration host factor subunit alpha and Tyrosine recombinase XerC. Furthermore, four drug-like compounds showing potential inhibitory effects against both target proteins were identified. Subsequently, molecular docking analysis was conducted involving these targets and the compounds. This initial study provides the list of novel targets against S. dysenteriae. Conclusively, future in vitro investigations could validate our in-silico findings and uncover potential therapeutic drugs for combating bacillary dysentery infection.

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Prevalence and Antimicrobial Resistance Patterns of <i>Shigella</i> in Ethiopia from 2000 to 2018: A Critical Review

Cited by 2 publications

References 15 publications

Isolation, Identification and Antibiotic Resistance of Different Clinical Isolates in Savar Area, Bangladesh

Isolation, Identification and Antibiotic Resistance of Different Clinical Isolates in Savar Area, Bangladesh

An integrated in-silico approach for drug target identification in human pathogen Shigella dysenteriae

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