Rapid, label-free pathogen identification system for multidrug-resistant bacterial wound infection detection on military members in the battlefield

Optimization and Validation of an FTIR-based, All-in-one System for Viable MDR Bacteria Detection in Combat-related Wound Infection

INTRODUCTION

The U.S. Military members experiencing combat-related injuries have a higher chance of developing infections by multidrug-resistant (MDR) bacteria at admission to military hospitals. MDR wound infections result in higher amputation rates and greater risks for subsequent or chronic infections that require readmission or extended stay in the hospital. Currently, there is no FDA-clear, deployable early diagnostic system for suitable field use.We are reporting our efforts to improve a previously developed Rapid Label-free Pathogen Identification (RAPID) system to detect viable MDR bacteria in wound infections and perform antibiotic susceptibility testing (AST). Specifically, we added multiplex and automation capability and significantly simplified the sample preparation process. A functional prototype of the improved system was built, and its performance was validated using a variety of lab-prepared spiked samples and real-world samples.

MATERIALS AND METHODS

To access the baseline performance of the improved RAPID system in detecting bacteria presence, we selected 17 isolates, most of them from blood or wound infections, and prepared mono-strain spiked samples at 104 to 106 cfu/mL concentration. These samples were processed and analyzed by the RAPID system. To demonstrate the AST capability of the system, we selected 6 strains against 6 different antibiotics and compared the results from the system with the ones from the gold standard method.To validate the system's performance with real-world samples, we first investigated its performance on 3 swab samples from epicutaneous methicillin-resistant Staphylococcus aureus-exposed mouse model. The AST results from our system were compared with the ones from the gold standard method. All animal experiments were approved by the Johns Hopkins University Animal Care and Use Committee (Protocol No. MO21M378). Then, we obtained swab samples from 7 atopic dermatitis (AD) patients and compared our AST results with the ones from the gold standard method. The human subject protocol was approved by the Johns Hopkins Medicines Institutional Review Boards (Study No. CR00043438/IRB00307926) and by USAMRDC (Proposal Log Number/Study Number 20000251).

RESULTS

High-quality data were obtained from the spiked samples of all 17 strains. A quantitative analysis model built using these data achieved 94% accuracy in predicting the species ID in 8 unknown samples. The AST results on the spiked samples had shown 100% matching with the gold standard method. Our system successfully detects the presence/absence of viable bacteria in all 3 mouse and 7 AD patient swab samples. Our system shows 100% and 85.7% (6 out of 7) accuracy when compared to the oxacillin susceptibility testing results for the mouse and the AD patient swabs, respectively.

CONCLUSIONS

Our system has achieved excellent performance in detecting viable bacteria presence and in performing AST in a multiplex, automated, and easy-to-operate manner, on both lab-prepared and real samples. Our results have shown a path forward to a rapid (sample-to-answer time ≤3 hours), accurate, sensitive, species-specific, and portable system to detect the presence of MDR combat-related wound infections in the field environment. Our future efforts involve ruggedizing the RAPID system and evaluating performance under relevant environmental conditions.

Targeted metagenomic assessment reflects critical colonization in battlefield injuries

IMPORTANCE

Microbial contamination in combat wounds can lead to opportunistic infections and adverse outcomes. However, current microbiological detection has a limited ability to capture microbial functional genes. This work describes the application of targeted metagenomic sequencing to profile wound bioburden and capture relevant wound-associated signatures for clinical utility. Ultimately, the ability to detect such signatures will help guide clinical decisions regarding wound care and management and aid in the prediction of wound outcomes.

Spectroscopic Identification of Bacteria Resistance to Antibiotics by Means of Absorption of Specific Biochemical Groups and Special Machine Learning Algorithm

FTIR (Fourier transform infrared spectroscopy) is one analytical technique of the absorption of infrared radiation. FTIR can also be used as a tool to characterize profiles of biomolecules in bacterial cells, which can be useful in differentiating different bacteria. Considering that different bacterial species have different molecular compositions, it will then result in unique FTIR spectra for each species and even bacterial strains. Having this important tool, here, we have developed a methodology aimed at refining the analysis and classification of the FTIR absorption spectra obtained from samples of Staphylococcus aureus, with the implementation of machine learning algorithms. In the first stage, the system conforming to four specified species groups, Control, Amoxicillin induced (AMO), Gentamicin induced (GEN), and Erythromycin induced (ERY), was analyzed. Then, in the second stage, five hidden samples were identified and correctly classified as with/without resistance to induced antibiotics. The total analyses were performed in three windows, Carbohydrates, Fatty Acids, and Proteins, of five hundred spectra. The protocol for acquiring the spectral data from the antibiotic-resistant bacteria via FTIR spectroscopy developed by Soares et al. was implemented here due to demonstrating high accuracy and sensitivity. The present study focuses on the prediction of antibiotic-induced samples through the implementation of the hierarchical cluster analysis (HCA), principal component analysis (PCA) algorithm, and calculation of confusion matrices (CMs) applied to the FTIR absorption spectra data. The data analysis process developed here has the main objective of obtaining knowledge about the intrinsic behavior of S. aureus samples within the analysis regions of the FTIR absorption spectra. The results yielded values with 0.7 to 1 accuracy and high values of sensitivity and specificity for the species identification in the CM calculations. Such results provide important information on antibiotic resistance in samples of S. aureus bacteria for potential application in the detection of antibiotic resistance in clinical use.

Military Medicine and Medical Research as a Source of Inspiration and Innovation to Solve National Security and Health Challenges in the 21st Century

The history of military medicine and research is rife with examples of novel treatments and new approaches to heal and cure soldiers and others impacted by war's devastation. In the 21st century, new threats, like climate change, are combined with traditional threats, like geopolitical conflict, to create novel challenges for our strategic interests. Extreme and inaccessible environments provide heightened risks for warfighter exposure to dangerous bacteria, viruses, and fungi, as well as exposure to toxic substances and extremes of temperature, pressure, or both providing threats to performance and eroding resilience. Back home, caring for our veterans is also a health-care priority, and the diseases of veterans increasingly overlap with the health needs of an aging society. These trends of climate change, politics, and demographics suggest performance evaluation and resilience planning and response are critical to assuring both warfighter performance and societal health. The Cleveland ecosystem, comprising several hospitals, a leading University, and one of the nation's larger Veteran's Health Administration systems, is ideal for incubating and understanding the response to these challenges. In this review, we explore the interconnections of collaborations between Defense agencies, particularly Air Force and Army and academic medical center-based investigators to drive responses to the national health security challenges facing the United States and the world.

Bacteriological profile of wound swab and their antibiogram pattern in a tertiary care hospital, Saudi Arabia

OBJECTIVES

To assess the microbial profile of wound infection and their antibiogram pattern.

METHODS

A retrospective study was carried out at King Abdulaziz University Hospital, Jeddah Saudi Arabia between December 2021 and July 2022 comprising data related to demographic, microbial profile and antibiotic sensitivity pattern of wound infection-suspected cases.

RESULTS

A total of 305 wound swabs were collected; of which 56.1% showed microbial growth. Among 187 microbial isolates, 62% were gram-negative bacteria, 30.5% were gram-positive bacteria and 7.5% were fungi. Staphylococcus aureus was the prevailing isolates 17.1%, followed by Klebsiella pneumoniae and Pseudomonas aeruginosa, each with 13.9% and Escherichia coli with 12.8 %. Providencia sp with 0.1% was the least isolated bacteria. Out of 173 bacterial isolates, 46.8% were sensitive to antimicrobial agents tested, while 53.2% were resistant to one and more drug tested. Of these isolates, 22% were found to be the MDR bacteria. The highest MDR percentages was noted among Acinetobacter baumannii (70%) followed by Klebsiella pneumoniae (53.9%), Escherichia coli (25%) and Pseudomonas aeruginosa (19.2%) and the least by (12.5%) by Staphylococcus aureus. CONCLUSION: The microbial isolation rates from wound infection was high, with Staphylococcus aureus being the most prevalent. Considerable antimicrobial resistance rate to the commonly used antibiotics was discovered. Thus, regular monitoring of microbial profile and their antimicrobial sensitivity pattern in the study region in attempt to contain antimicrobial resistance is highly recommended.

Recent Advances in the Use of Molecular Methods for the Diagnosis of Bacterial Infections

Infections caused by bacteria have a major impact on public health-related morbidity and mortality. Despite major advances in the prevention and treatment of bacterial infections, the latter continue to represent a significant economic and social burden worldwide. The WHO compiled a list of six highly virulent multidrug-resistant bacteria named ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) responsible for life-threatening diseases. Taken together with Clostridioides difficile, Escherichia coli, Campylobacter spp., (C. jejuni and C. coli), Legionella spp., Salmonella spp., and Neisseria gonorrhoeae, all of these microorganisms are the leading causes of nosocomial infections. The rapid and accurate detection of these pathogens is not only important for the early initiation of appropriate antibiotic therapy, but also for resolving outbreaks and minimizing subsequent antimicrobial resistance. The need for ever-improving molecular diagnostic techniques is also of fundamental importance for improving epidemiological surveillance of bacterial infections. In this review, we aim to discuss the recent advances on the use of molecular techniques based on genomic and proteomic approaches for the diagnosis of bacterial infections. The advantages and limitations of each of the techniques considered are also discussed.