Shigellosis in Southeast Asia: A systematic review and meta-analysis

Rapid diagnostic tests and loop-mediated isothermal amplification method for the detection of Shigella species: A systematic review and meta-analysis

We meta-analyzed the diagnostic accuracy of rapid diagnostic tests (dipsticks) and loop-mediated isothermal amplification (LAMP) method to detect Shigella species. We searched MEDLINE, Embase, Web of Science and Google Scholar from inception to 2023 for studies reporting on the performance of Shigella dipstick and LAMP tests compared with culture or polymerase chain reaction (PCR). Our search identified 2618 studies, of which fourteen met the inclusion criteria for the systematic review. Ten studies covering 4056 tests (from twelve countries) were included in the meta-analysis. The overall pooled sensitivity and specificity were 98% (95% CI: 94-100) and 97% (95% CI: 92-99), respectively. Pooled sensitivity and specificity of dipsticks were 95% and 98%, respectively. In contrast, LAMP showed higher pooled sensitivity (100%) and diagnostic odds ratio (431752), but similar specificity (97%). LAMP and dipstick tests exhibited promising performance, suggesting that they could be useful for assisting in the diagnosis of shigellosis.

Vibriosis in South Asia: A systematic review and meta-analysis

OBJECTIVES

South Asia remains home to foodborne diseases caused by the Vibrio species. We aimed to compile and update information on the epidemiology of vibriosis in South Asia.

METHODS

For this systematic review and meta-analysis, we searched PubMed, Web of Science, EMBASE, and Google Scholar for studies related to vibriosis in South Asia published up to May 2023. A random-effects meta-analysis was used to estimate the pooled isolation rate of non-cholera-causing Vibrio species.

RESULTS

In total, 38 studies were included. Seven of these were case reports and 22 were included in the meta-analysis. The reported vibriosis cases were caused by non-O1/non-O139 V. cholerae, V. parahaemolyticus, V. fluvialis, and V. vulnificus. The overall pooled isolation rate was 4.0% (95% confidence interval [CI] 3.0-5.0%) in patients with diarrhea. Heterogeneity was high (I2 = 98.0%). The isolation rate of non-O1/non-O139 V. cholerae, V. parahaemolyticus, and V. fluvialis were 9.0 (95% CI 7.0-10.0%), 1.0 (95% CI 1.0-2.0%), and 2.0 (95% CI: 1.0-3.0%), respectively. Regarding V. parahaemolyticus, O3:K6 was the most frequently isolated serotype. Cases peaked during summer. Several studies reported antibiotic-resistant strains and those harboring extended-spectrum beta-lactamases genes.

CONCLUSIONS

This study demonstrates a high burden of infections caused by non-cholera-causing Vibrio species in South Asia.

Genetic evidence strengthens the bidirectional connection between gut microbiota and Shigella infection: insights from a two-sample Mendelian randomization study

Background

In recent investigations, substantial strides have been made in the precise modulation of the gut microbiota to prevent and treat a myriad of diseases. Simultaneously, the pressing issue of widespread antibiotic resistance and multidrug resistance resulting from Shigella infections demands urgent attention. Several studies suggest that the antagonistic influence of the gut microbiota could serve as a novel avenue for impeding the colonization of pathogenic microorganisms or treating Shigella infections. However, conventional research methodologies encounter inherent challenges in identifying antagonistic microbial agents against Shigella, necessitating a comprehensive and in-depth analysis of the causal relationship between Shigella infections and the gut microbiota.

Materials and methods

Utilizing the aggregated summary statistics from Genome-Wide Association Studies (GWAS), we conducted Mendelian Randomization (MR) analyses encompassing 18,340 participants to explore the interplay between the gut microbiota and Shigella infections. This investigation also involved 83 cases of Shigella infection patients and 336,396 control subjects. In the positive strand of our findings, we initially performed a preliminary analysis using the Inverse Variance Weighting (IVW) method. Subsequently, we undertook sensitivity analyses to assess the robustness of the results, addressing confounding factors' influence. This involved employing the Leave-One-Out method and scrutinizing funnel plots to ensure the reliability of the MR analysis outcomes. Conclusively, a reverse MR analysis was carried out, employing the Wald ratio method due to the exposure of individual Single Nucleotide Polymorphisms (SNPs). This was undertaken to explore the plausible associations between Shigella infections and genetically predicted compositions of the gut microbiota.

Results

In this study, we employed 2,818 SNPs associated with 211 species of gut microbiota as instrumental variables (IVs). Through IVW analysis, our positive MR findings revealed a significant negative correlation between the occurrence of Shigella infections and the phylum Tenericutes (OR: 0.18, 95% CI: 0.04-0.74, p = 0.02), class Mollicutes (OR: 0.18, 95% CI: 0.04-0.74, p = 0.02), genus Intestinimonas (OR: 0.16, 95% CI: 0.04-0.63, p = 0.01), genus Gordonibacter (OR: 0.39, 95% CI: 0.16-0.93, p = 0.03), and genus Butyrivibrio (OR: 0.44, 95% CI: 0.23-0.87, p = 0.02). Conversely, a positive correlation was observed between the occurrence of Shigella infections and genus Sutterella (OR: 10.16, 95% CI: 1.87-55.13, p = 0.01) and genus Alistipes (OR: 12.24, 95% CI: 1.71-87.34, p = 0.01). In sensitivity analyses, utilizing MR-Egger regression analysis and MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) detection, all outcomes demonstrated robust stability. Simultaneously, in the reverse MR analysis, Shigella infections resulted in an upregulation of four bacterial genera and a downregulation of three bacterial genera.

Conclusion

In summation, the MR analysis outcomes corroborate the presence of bidirectional causal relationships between the gut microbiota and Shigella infections. This study not only unveils novel perspectives for the prevention and treatment of Shigella infections but also furnishes fresh insights into the mechanistic underpinnings of how the gut microbiota contributes to the pathogenesis of Shigella infections. Consequently, the established dual causal association holds promise for advancing our understanding and addressing the complexities inherent in the interplay between the gut microbiota and Shigella infections, thereby paving the way for innovative therapeutic interventions and preventive strategies in the realm of Shigella-related diseases.

Animal and In Vitro Models as Powerful Tools to Decipher the Effects of Enteric Pathogens on the Human Gut Microbiota

Examining the interplay between intestinal pathogens and the gut microbiota is crucial to fully comprehend the pathogenic role of enteropathogens and their broader impact on human health. Valid alternatives to human studies have been introduced in laboratory practice to evaluate the effects of infectious agents on the gut microbiota, thereby exploring their translational implications in intestinal functionality and overall health. Different animal species are currently used as valuable models for intestinal infections. In addition, considering the recent advances in bioengineering, futuristic in vitro models resembling the intestinal environment are also available for this purpose. In this review, the impact of the main human enteropathogens (i.e., Clostridioides difficile, Campylobacter jejuni, diarrheagenic Escherichia coli, non-typhoidal Salmonella enterica, Shigella flexneri and Shigella sonnei, Vibrio cholerae, and Bacillus cereus) on intestinal microbial communities is summarized, with specific emphasis on results derived from investigations employing animal and in vitro models.