Multiplex PCR Based Strategy for Detection of Fungal Pathogen DNA in Patients with Suspected Invasive Fungal Infections

Molecular strategy for the direct detection and identification of the most common fungal community in cerumen specimens by multiplex PCR

Introduction. Otomycosis is a superficial fungal infection that is responsible for approximately 9-27 % of otitis externa. However, fungal communities in otomycosis are varied, but Aspergillus spp. and Candida spp. are the most common causes of this infection.Hypothesis Statement. The multiplex PCR assay is postulated to be able to directly detect more than one fungal genus in cerumen specimens.Aim. This study aimed to develop and evaluate the role of the multiplex PCR assay in detecting the most common genus of fungi that cause otomycosis directly from the cerumen specimens.Methodology. To detect Candida and Aspergillus/Penicillium genera, three pairs of primers, including pan-fungal, pan-Candida, and pan-Aspergillus/Penicillium, were used in a multiplex PCR. In order to evaluate the performance and reproducibility of the multiplex PCR. the cerumen of 140 patients suspected of otomycosis were investigated.Results. Pan-Candida and pan-Aspergillus/Penicillium primers were designed to amplify the ITS1-5.8S-ITS2 region and the β-tubulin gene, respectively. In the multiplex PCR assay, 64 (47.40 %) and 118 (87.40 %) specimens were positive with pan-Candida and pan-Aspergillus/Penicillium primers, respectively. Double amplicon bands of Candida and Aspergillus were obtained in 51 (37.77 %) specimens. In the culture method, yeast (n=18, 13.33 %) and mould (n=117, 86.66 %) were isolated from 135 cerumen specimens. The sensitivity, specificity, and positive and negative predictive values of the multiplex PCR assays using culture method results as the gold standard were determined to be 94, 33, 97, and 22 %, respectively.Conclusion. In our study, multiplex PCR assays enabled simultaneous detection of two common genera of the causative agent of otomycosis in a cerumen specimen. Regarding the high sensitivity of the first step of the multiplex PCR assay, this assay may be used for the direct detection of Candida and Aspergillus genera in other clinical specimens.

A Comprehensive Review of Identification Methods for Pathogenic Yeasts: Challenges and Approaches

Given the increasing incidence of yeast infections and the presence of drug-resistant isolates, accurate identification of the pathogenic yeasts is essential for the management of yeast infections. In this review, we tried to introduce the routine and novel techniques applied for yeast identification. Laboratory identification methods of pathogenic yeast are classified into three categories; I. conventional methods, including microscopical and culture-base methods II. biochemical/physiological-processes methods III. molecular methods. While conventional and biochemical methods require more precautions and are not specific in some cases, molecular diagnostic methods are the optimum tools for diagnosing pathogenic yeasts in a short time with high accuracy and specificity, and having various methods that cover different purposes, and affordable costs for researchers. Nucleotide sequencing is a reference or gold standard for identifying pathogenic yeasts. Since it is an expensive method, it is not widely used in developing countries. However, novel identification techniques are constantly updated, and we recommend further studies in this field. The results of this study will guide researchers in finding more accurate diagnostic method(s) for their studies in a short period of time.

Fungal Infections Identified with Multiplex PCR in Severe COVID-19 Patients during Six Pandemic Waves

Background and Objectives: With an increasing number of severe COVID-19 cases presenting with secondary fungal infections, this study aimed to determine the prevalence of fungal co-infections in severe COVID-19 patients across the six waves, identify the most common fungal pathogens associated with severe COVID-19, and explore any potential links between patient characteristics, therapeutic strategies, and the prevalence and type of fungal infection. Materials and Methods: A retrospective analysis was conducted on severe COVID-19 patients admitted to the Infectious Diseases and Pulmonology Hospital, "Victor Babes", Romania, between March 2020 and August 2022. Samples were collected from respiratory specimens, blood, and urine, after which a standard nucleic acid extraction protocol was employed. Patients were divided into groups with and without fungal infections, identified using multiplex PCR. The groups were compared based on demographic data, comorbidities, pandemic wave number, and clinical outcomes. Results: Out of 288 patients, 96 (33.3%) had fungal infections, with Candida spp. being the most common. Patients with fungal infections had higher rates of obesity (35.4% vs. 21.4%, p = 0.010) and a higher Charlson comorbidity index (CCI > 2) (37.5% vs 25.0%, p = 0.027). Ventilator use was significantly higher in the fungal infection group (45.8% vs. 18.8%; p < 0.001), as was ICU admission (39.6% vs. 26.6%; p = 0.024) and mortality (32.3% vs 12.0%; p < 0.001). The distribution of different fungal species varied across the pandemic waves, with no statistical significance (p = 0.209). The mortality risk notably increased with the degree of drug resistance (OR for three or more drug resistances = 6.71, p < 0.001). The second, fourth, and fifth pandemic waves were significantly associated with higher mortality risk (OR = 3.72, 3.61, and 4.08, respectively, all p < 0.001). Aspergillus spp. and Mucor spp. infections were significantly associated with increased mortality risk (OR = 4.61 and 6.08, respectively, both p < 0.001). Conclusions: Our study indicates a significant presence of fungal co-infections among severe COVID-19 patients that is associated with increased morbidity and mortality, particularly in patients with drug-resistant infections. These findings underline the necessity for comprehensive diagnostic approaches and tailored treatment strategies in managing COVID-19 patients, especially during specific pandemic waves and in patients with particular fungal infections. Further research is required to understand the implications of these co-infections and their management.

Diagnosis of invasive fungal infections: challenges and recent developments

BACKGROUND

The global burden of invasive fungal infections (IFIs) has shown an upsurge in recent years due to the higher load of immunocompromised patients suffering from various diseases. The role of early and accurate diagnosis in the aggressive containment of the fungal infection at the initial stages becomes crucial thus, preventing the development of a life-threatening situation. With the changing demands of clinical mycology, the field of fungal diagnostics has evolved and come a long way from traditional methods of microscopy and culturing to more advanced non-culture-based tools. With the advent of more powerful approaches such as novel PCR assays, T2 Candida, microfluidic chip technology, next generation sequencing, new generation biosensors, nanotechnology-based tools, artificial intelligence-based models, the face of fungal diagnostics is constantly changing for the better. All these advances have been reviewed here giving the latest update to our readers in the most orderly flow.

MAIN TEXT

A detailed literature survey was conducted by the team followed by data collection, pertinent data extraction, in-depth analysis, and composing the various sub-sections and the final review. The review is unique in its kind as it discusses the advances in molecular methods; advances in serology-based methods; advances in biosensor technology; and advances in machine learning-based models, all under one roof. To the best of our knowledge, there has been no review covering all of these fields (especially biosensor technology and machine learning using artificial intelligence) with relevance to invasive fungal infections.

CONCLUSION

The review will undoubtedly assist in updating the scientific community's understanding of the most recent advancements that are on the horizon and that may be implemented as adjuncts to the traditional diagnostic algorithms.

Invasive Mold Infections in Children: Navigating Troubled Waters with a Broken Compass

Incidence of invasive mold infections in children, while rare, is increasing as the population of high-risk patients expands, including premature infants, pediatric patients undergoing treatment for hematological malignancies, or recipients of allogeneic hematologic stem cell transplants. The infectious agents, including Aspergillus spp., Mucorales, and other molds, are especially difficult to treat and have serious morbidity and high mortality. Clinicians must maintain a high index of suspicion for invasive mold infections in at-risk patients. Diagnosis of invasive mold infections is complicated by difficulties isolating pathogens on culture, but progress is being made in immunological and molecular diagnostic technologies. Treatment in children is challenging; no randomized controlled trials exist. There is a growing body of data on treatment, specifically on safer antifungal agents, including indications for treatment, spectrum of coverage, pharmacokinetics for different ages, and pharmacodynamic targets associated with therapeutic success. However, pediatricians must often extrapolate from adult data. In this review, we aim to harmonize the existing body of literature on invasive mold infections in children, covering epidemiology, clinical presentations, diagnostic methods, and principles of management.

A cell wall-targeted organic-inorganic hybrid nano-catcher for ultrafast capture and SERS detection of invasive fungi

Due to the extended culture period and various inconveniences in vitro culture, the detection of invasive fungi is rather difficult, leading to high mortality rates of the diseases caused by them. It is, however, crucial for clinical therapy and lowering patient mortality to quickly identify invasive fungus from clinical specimens. A promising non-destructive method for finding fungi is surface-enhanced Raman scattering (SERS), however, its substrate has a low level of selectivity. Clinical sample components can obstruct the target fungi's SERS signal on account of their complexity. Herein, an MNP@PNIPAMAA hybrid organic-inorganic nano-catcher was created by using ultrasonic-initiated polymerization. The caspofungin (CAS), a fungus cell wall-targeting drug, is used in this study. We investigated MNP@PNIPAMAA-CAS as a technique to rapidly extract fungus from complex samples under 3 s. SERS could subsequently be used to instantly identify the fungi that were successfully isolated with an efficacy rate of about 75%. The entire process took just 10 min. This method is an important breakthrough that might be advantageous in terms of the rapid detection of invasive fungi.

Optimization of a Quantitative PCR Methodology for Detection of Aspergillus spp. and Rhizopus arrhizus

Introduction

Multiplex quantitative polymerase chain reaction (qPCR) methods for the detection of Aspergillus spp. based only on SYBR Green and melting curve analysis of PCR products are difficult to develop because most targets are located within ITS regions. The aim of this study was to adapt our previously developed methodology based on a multiplex PCR assay coupled with GeneScan analysis to provide a qPCR method.

Methods

A SYBR Green-based real-time PCR assay was optimized to detect A. fumigatus, A. flavus, A. niger, A. terreus, and R. arrhizus in a multiplex assay and applied to cultured fungi and spiked plasma.

Results

Different melting temperatures allowed identification of all five pathogens and discrimination between them, even in samples with low amounts of fungal gDNA (from 1.3 to 33.0 pg/μL), which has been reported previously as problematic. No false-positive results were obtained for non-target species, including bacteria and human DNA. This method allowed detection of fungal pathogens in human plasma spiked with fungal DNA and in coinfections of A. niger/R. arrhizus.

Discussion

This work provides evidence for the use of a qPCR multiplex method based on SYBR Green and melting curve analysis of PCR products for the detection of A. fumigatus, A. flavus, A. niger, A. terreus, and R. arrhizus. The proposed method is simpler and less expensive than available kits based on fluorescent probes and can be used for aiding diagnosis of the most relevant invasive filamentous fungi, particularly in low-income health care institutions.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40291-022-00595-1.

The Impact of Multiplex PCR in Diagnosing and Managing Bacterial Infections in COVID-19 Patients Self-Medicated with Antibiotics

The multiplex PCR is a powerful and efficient tool that was widely used during the COVID-19 pandemic to diagnose SARS-CoV-2 infections and that has applications for bacterial identification, as well as determining bacterial resistance to antibiotics. Therefore, this study aimed to determine the usability of multiplex PCR, especially in patients self-medicated with antibiotics, where bacterial cultures often give false-negative results. A cross-sectional study was developed in two COVID-19 units, where 489 eligible patients were included as antibiotic takers and non-antibiotic takers. Antibiotic takers used mostly over-the-counter medication; they suffered significantly more chronic respiratory conditions and were self-medicated most often with cephalosporins (41.4%), macrolide (23.2%), and penicillin (19.7%). The disease severity in these patients was significantly higher than in non-antibiotic takers, and bacterial superinfections were the most common finding in the same group (63.6%). Antibiotic takers had longer hospital and ICU admissions, although the mortality rate was not significantly higher than in non-antibiotic takers. The most common bacteria involved in secondary infections were Staphylococcus aureus (22.2%), Pseudomonas aeruginosa (27.8%), and Klebsiellaspp (25.0%). Patients self-medicating with antibiotics had significantly higher rates of multidrug resistance. The multiplex PCR test was more accurate in identifying multidrug resistance and resulted in a quicker initiation of therapeutic antibiotics compared with instances where a bacterial culture was initially performed, with an average of 26.8 h vs. 40.4 h, respectively. The hospital stay was also significantly shorter by an average of 2.5 days when PCR was used as an initial assessment tool for secondary bacterial infections. When adjusted for age, COVID-19 severity, and pulmonary disease, over-the-counter use of antibiotics represented a significant independent risk factor for a prolonged hospitalization (AOR = 1.21). Similar findings were observed for smoking status (AOR = 1.44), bacterial superinfection (AOR = 1.52), performing only a conventional bacterial culture (AOR = 1.17), and a duration of more than 48 h for bacterial sampling from the time of hospital admission (AOR = 1.36). Multiplex PCR may be a very effective method for diagnosing secondary bacterial infections in COVID-19 individuals self-medicating with antibiotics. Utilizing this strategy as an initial screen in COVID-19 patients who exhibit signs of sepsis and clinical deterioration will result in a faster recovery time and a shorter period of hospitalization.

Fungal infections diagnosis - Past, present and future

Despite the scientific advances observed in the recent decades and the emergence of new methodologies, the diagnosis of systemic fungal infections persists as a problematic issue. Fungal cultivation, the standard method that allows a proven diagnosis, has numerous disadvantages, as low sensitivity (only 50% of the patients present positive fungal cultures), and long growth time. These are factors that delay the patient's treatment and, consequently, lead to higher hospital costs. To improve the accuracy and quickness of fungal infections diagnosis, several new methodologies attempt to be implemented in clinical microbiology laboratories. Most of these innovative methods are independent of pathogen isolation, which means that the diagnosis goes from being considered proven to probable. In spite of the advantage of being culture-independent, the majority of the methods lack standardization. PCR-based methods are becoming more and more commonly used, which has earned them an important place in hospital laboratories. This can be perceived now, as PCR-based methodologies have proved to be an essential tool fighting against the COVID-19 pandemic. This review aims to go through the main steps of the diagnosis for systemic fungal infection, from diagnostic classifications, through methodologies considered as "gold standard", to the molecular methods currently used, and finally mentioning some of the more futuristic approaches.

Future Directions for Clinical Respiratory Fungal Research

There has been a growing appreciation of the importance of respiratory fungal diseases in recent years, with better understanding of their prevalence as well as their global distribution. In step with the greater awareness of these complex infections, we are currently poised to make major advances in the characterization and treatment of these fungal diseases, which in itself is largely a consequence of post-genomic technologies which have enabled rational drug development and a path towards personalized medicines. These advances are set against a backdrop of globalization and anthropogenic change, which have impacted the world-wide distribution of fungi and antifungal resistance, as well as our built environment. The current revolution in immunomodulatory therapies has led to a rapidly evolving population at-risk for respiratory fungal disease. Whilst challenges are considerable, perhaps the tools we now have to manage these infections are up to this challenge. There has been a welcome acceleration of the antifungal pipeline in recent years, with a number of new drug classes in clinical or pre-clinical development, as well as new focus on inhaled antifungal drug delivery. The "post-genomic" revolution has opened up metagenomic diagnostic approaches spanning host immunogenetics to the fungal mycobiome that have allowed better characterization of respiratory fungal disease endotypes. When these advances are considered together the key challenge is clear: to develop a personalized medicine framework to enable a rational therapeutic approach.

Deep convolutional neural network: a novel approach for the detection of Aspergillus fungi via stereomicroscopy

Fungi of the genus Aspergillus are ubiquitously distributed in nature, and some cause invasive aspergillosis (IA) infections in immunosuppressed individuals and contamination in agricultural products. Because microscopic observation and molecular detection of Aspergillus species represent the most operator-dependent and time-intensive activities, automated and cost-effective approaches are needed. To address this challenge, a deep convolutional neural network (CNN) was used to investigate the ability to classify various Aspergillus species. Using a dissecting microscopy (DM)/stereomicroscopy platform, colonies on plates were scanned with a 35× objective, generating images of sufficient resolution for classification. A total of 8,995 original colony images from seven Aspergillus species cultured in enrichment medium were gathered and autocut to generate 17,142 image crops as training and test datasets containing the typical representative morphology of conidiophores or colonies of each strain. Encouragingly, the Xception model exhibited a classification accuracy of 99.8% on the training image set. After training, our CNN model achieved a classification accuracy of 99.7% on the test image set. Based on the Xception performance during training and testing, this classification algorithm was further applied to recognize and validate a new set of raw images of these strains, showing a detection accuracy of 98.2%. Thus, our study demonstrated a novel concept for an artificial-intelligence-based and cost-effective detection methodology for Aspergillus organisms, which also has the potential to improve the public's understanding of the fungal kingdom.

Molecular Diagnosis of Yeast Infections

PURPOSE OF REVIEW

The use of molecular tests to aid the diagnosis of invasive yeast infection, in particular invasive candidosis, has been described for over two decades, yet widespread application is limited, and diagnosis remains heavily dependent on classical microbiology. This article will review developments from the past decade in attempt to build on existing knowledge. It will highlight clinical performance and limitations while reviewing developments on recognized procedures; it will also provide insight into novel approaches incorporated in response to clinical demand (e.g. C. auris and antifungal resistance) or technological advances (e.g. next-generation sequencing).

RECENT FINDINGS

Limited methodological standardization and, until recently, unavailability of commercial options have hindered the integration of molecular diagnostics for yeasts. The development of certain, novel commercial methods has received considerable evaluation allowing a greater understanding of individual assay performance, but widespread multicentre evaluation of most commercial kits is lacking. The detection of emerging pathogens (e.g. C. auris) has been enhanced by the development of molecular tests. Molecular methods are providing a better understanding of the mycobiome, mechanisms of resistance and epidemiology/phylogeny.

SUMMARY

Despite over two decades of use, the incorporation of molecular methods to enhance the diagnosis of yeast infections remains limited to certain specialist centres. While the development of commercial tests will provide stimulus for broader application, further validation and reduced costs are required. Over the same period of time, Aspergillus PCR has become more widely accepted driven by international efforts to standardize methodology; it is critical that yeast PCR follows suit. Next-generation sequencing will provide significant information on the mycobiome, antifungal resistance mechanism and even broad-range detection directly from the specimen, which may be critical for the molecular detection of yeasts other than Candida species, which is currently limited.