The impact of antibiotic resistance on the rampant spread of infectious diseases in Pakistan: Insights from a narrative review

Background and Aims

Antibiotic resistance (ABR) is a global public health emergency which has seen an uptick in low- to middle-income countries in recent times due to a plethora of aggravating factors and has led to a whole host of setting-specific pathogens registering high rates of resistance, causing outbreaks with graver mortality and morbidity. This review analyzes available literature to determine the causes and effects of ABR and recommend solutions to the problem in a Pakistani setting.

Methods

Sources for this narrative review were identified via electronic databases using keyword search methods. The information was retrieved using databases such as PubMed and Science Direct. Additionally, websites such as CDC and World Health Organization were used to attain pertinent information. All the sources were selected as per their relevance and appropriateness toward the purpose of this review.

Results

This review details the causes by dividing them into three primary strata, namely (1) under-regulation, (2) over-prescription and self-medication, and (3) lack of medical stewardship. This is made much graver when the COVID-19 pandemic and the subsequent erratic treatment response is considered, with the pandemic augmenting already high levels of consumption. These factors have led a cascade of effects including, but not limited to, a considerable increase in ABR in pathogens to first-line drugs.

Conclusion

ABR is a serious and growing issue which will result in undesirable personal, local, and national consequences if unchecked. Mitigation and reversal of this trend is necessary by developing existing programs and investing in novel therapies and pharmaceutical research and strengthening regulatory policies and mechanisms.

Machine Learning Techniques for Antimicrobial Resistance Prediction of Pseudomonas Aeruginosa from Whole Genome Sequence Data

AIM

Due to the growing availability of genomic datasets, machine learning models have shown impressive diagnostic potential in identifying emerging and reemerging pathogens. This study aims to use machine learning techniques to develop and compare a model for predicting bacterial resistance to a panel of 12 classes of antibiotics using whole genome sequence (WGS) data of Pseudomonas aeruginosa.

METHOD

A machine learning technique called Random Forest (RF) and BioWeka was used for classification accuracy assessment and logistic regression (LR) for statistical analysis.

RESULTS

Our results show 44.66% of isolates were resistant to twelve antimicrobial agents and 55.33% were sensitive. The mean classification accuracy was obtained ≥98% for BioWeka and ≥96 for RF on these families of antimicrobials. Where ampicillin was 99.31% and 94.00%, amoxicillin was 99.02% and 95.21%, meropenem was 98.27% and 96.63%, cefepime was 99.73% and 98.34%, fosfomycin was 96.44% and 99.23%, ceftazidime was 98.63% and 94.31%, chloramphenicol was 98.71% and 96.00%, erythromycin was 95.76% and 97.63%, tetracycline was 99.27% and 98.25%, gentamycin was 98.00% and 97.30%, butirosin was 99.57% and 98.03%, and ciprofloxacin was 96.17% and 98.97% with 10-fold-cross validation. In addition, out of twelve, eight drugs have found no false-positive and false-negative bacterial strains.

CONCLUSION

The ability to accurately detect antibiotic resistance could help clinicians make educated decisions about empiric therapy based on the local antibiotic resistance pattern. Moreover, infection prevention may have major consequences if such prescribing practices become widespread for human health.

Synergistic Activity of Tetrandrine and Colistin against mcr-1-Harboring Escherichia coli

Before the emergence of plasmid-mediated colistin resistance, colistin was once considered the last drug of choice for infections caused by carbapenem-resistant bacteria. Currently, researchers are relentlessly exploring possible alternative therapies that could efficiently curb the spread of drug resistance. In this study, we aim to investigate the synergistic antibacterial activity of tetrandrine in combination with colistin against mcr-1-harboring Escherichia coli. We examined the antibacterial activity of tetrandrine in combination with colistin in vivo and in vitro and examined the bacterial cells by fluorescence, scanning, and transmission electron microscopy (TEM) to explore their underlying mechanism of action. We further performed a computational analysis of MCR-1 protein and tetrandrine to determine the interaction interface of these two molecules. We confirmed that neither colistin nor tetrandrine could, on their own, inhibit the growth of mcr-1-positive E. coli. However, in combination, tetrandrine synergistically enhanced colistin activity to inhibit the growth of E. coli both in vivo and in vitro. Similarly, molecular docking showed that tetrandrine interacted with the three crucial amino acids of the MCR-1 protein in the active site, which might inhibit MCR-1 from binding to its substrates, cause MCR-1 to lose its ability to confer resistance. This study confirmed that tetrandrine and colistin have the ability to synergistically overcome the issue of colistin resistance in mcr-1-harboring E. coli.

Whole-Genome Sequencing of a Colistin-Resistant Acinetobacter baumannii Strain Isolated at a Tertiary Health Facility in Pretoria, South Africa

BACKGROUND

Acinetobacter baumannii's (A. baumannii) growing resistance to all available antibiotics is of concern. The study describes a colistin-resistant A. baumannii isolated at a clinical facility from a tracheal aspirate sample. Furthermore, it determines the isolates' niche establishment ability within the tertiary health facility.

METHODS

An antimicrobial susceptibility test, conventional PCR, quantitative real-time PCR, phenotypic evaluation of the efflux pump, and whole-genome sequencing and analysis were performed on the isolate.

RESULTS

The antimicrobial susceptibility pattern revealed a resistance to piperacillin/tazobactam, ceftazidime, cefepime, cefotaxime/ceftriaxone, imipenem, meropenem, gentamycin, ciprofloxacin, trimethoprim/sulfamethoxazole, tigecycline, and colistin. A broth microdilution test confirmed the colistin resistance. Conventional PCR and quantitative real-time PCR investigations revealed the presence of adeB, adeR, and adeS, while mcr-1 was not detected. A MIC of 0.38 µg/mL and 0.25 µg/mL was recorded before and after exposure to an AdeABC efflux pump inhibitor. The whole-genome sequence analysis of antimicrobial resistance-associated genes detected beta-lactam: blaOXA-66; blaOXA-23; blaADC-25; blaADC-73; blaA1; blaA2, and blaMBL; aminoglycoside: aph(6)-Id; aph(3″)-Ib; ant(3″)-IIa and armA) and a colistin resistance-associated gene lpsB. The whole-genome sequence virulence analysis revealed a biofilm formation system and cell-cell adhesion-associated genes: bap, bfmR, bfmS, csuA, csuA/B, csuB, csuC, csuD, csuE, pgaA, pgaB, pgaC, and pgaD; and quorum sensing-associated genes: abaI and abaR and iron acquisition system associated genes: barA, barB, basA, basB, basC, basD, basF, basG, basH, basI, basJ, bauA, bauB, bauC, bauD, bauE, bauF, and entE. A sequence type classification based on the Pasteur scheme revealed that the isolate belongs to sequence type ST2.

CONCLUSIONS

The mosaic of the virulence factors coupled with the resistance-associated genes and the phenotypic resistance profile highlights the risk that this strain is at this South African tertiary health facility.

Antimicrobial resistance among GLASS priority pathogens from Pakistan: 2006-2018

Background

In 2018 Pakistan initiated its national antimicrobial resistance (AMR) surveillance aligned with Global Antimicrobial Surveillance System (GLASS). To complement this surveillance, we conducted a situational analysis of AMR rates among GLASS organisms in the country. Data from published studies and from antibiograms was compared and role of antibiograms as potential contributors to national AMR surveillance explored.

Methods

AMR rates for GLASS specified pathogen/antimicrobials combination from Pakistan were reviewed. Data sources included published studies (2006–2018) providing AMR rates from Pakistan (n = 54) as well as antibiograms (2011–2018) available on the Pakistan Antimicrobial Resistance Network (PARN) website. Resistance rates were categorized as follows: Very low: 0–10%, Low: 11–30%, Moderate: 30–50% and High: > 50%.

Results

Published data from hospital and community/laboratory-based studies report resistance rates of > 50% and 30–50% respectively to 3rd generation cephalosporins, fluoroquinolones and cotrimoxazole amongst Klebsiella pneumoniae and Escherichia coli. Carbapenem resistance rates amongst these organisms remained below 30%. High (> 50%) resistance was reported in Acinetobacter species to aminoglycosides and carbapenems among hospitalized patients. The evolution of ceftriaxone resistant Salmonella Typhi and Shigella species is reported. The data showed > 50% to fluoroquinolones amongst Neisseria gonorrhoeae and the spread of methicillin resistant Staphylococcus aureus (< 30%; 2008) to (> 50%; 2010) in hospital settings. Resistance reported in published studies aligned well with antibiogram data. The latter also captured a clear picture of evolution of resistance over the study period.

Conclusion

Both published studies as well antibiograms suggest high rates of AMR in Pakistan. Antibiogram data demonstrating steady increase in AMR highlight its potential role towards supplementing national AMR surveillance efforts particularly in settings where reach of national surveillance may be limited.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06795-0.

Antibiotic resistance in Pakistan: a systematic review of past decade

Background

During the last six decades, extensive use of antibiotics has selected resistant strains, increasing the rate of fatal infectious diseases, and exerting an economic burden on society. This situation is widely accepted as a global problem, yet its degree is not well elucidated in many regions of the world. Up till now, no systemic analysis of Antimicrobial resistance (AMR) in Pakistan has been published. The current study aims to describe the antibiotic-resistance scenario of Pakistan from human samples of the last 10 y, to find the gaps in surveillances and methodology and recommendations for researchers and prescribers founded on these outcomes.

Methods

Original research articles analyzed the pattern of Antibiotic resistance of any World Health Organization (WHO) enlisted priority pathogens in Pakistan (published onward 2009 till March 2020), were collected from PubMed, Google scholar, and PakMedi Net search engines. These articles were selected based on predefined inclusion and exclusion criteria. Data about the study characteristics and antibiotic-resistance for a given bacterium were excluded from literature. Antibiotic resistance to a particular bacterium was calculated as a median resistance with 95% Confidence Interval (CI).

Results

Studies published in the last 10 y showed that Urinary Tract Infection (UTI) is the most reported clinical diagnosis (16.1%) in Pakistan. E. coli were reported in 28 (30.11%) studies showing high resistance to antibiotics’ first line. Methicillin-resistant Staphylococcus aureus (MRSA) was found in 49% of S. aureus’ total reported cases. Phenotypic resistance pattern has mostly been evaluated by Disk Diffusion Method (DDM) (82.8%), taken Clinical Laboratory Standards Institute (CLSI) as a breakpoint reference guideline (in 79.6% studies). Only 28 (30.11%) studies have made molecular identification of the resistance gene. blaTEM (78.94% in Shigella spp) and blaNDM-1 (32.75% in Klebsiella spp) are the prominent reported resistant genes followed by VanA (45.53% in Enterococcus spp), mcr-1 (1.61% in Acinetobacter spp), and blaKPC-2 (31.67% in E. coli). Most of the studies were from Sindh (40.86%), followed by Punjab (35.48%), while Baluchistan’s AMR data was not available.

Conclusion

Outcomes of our study emphasize that most of the pathogens show high resistance to commonly used antibiotics; also, we find gaps in surveillances and breaches in methodological data. Based on these findings, we recommend the regularization of surveillance practice and precise actions to combat the region’s AMR.