Validation of High Resolution Melting Analysis (HRM) of the Amplified ITS2 Region for the Detection and Identification of Yeasts from Clinical Samples: Comparison with Culture and MALDI-TOF Based Identification

Second trimester vaginal Candida colonization among pregnant women attending antenatal care in Bukavu, Democratic Republic of the Congo: prevalence, clinical correlates, risk factors and pregnancy outcomes

Introduction

Vaginal Candida colonization (CC) can lead to vulvovaginal candidiasis, the second most prevalent vaginal condition worldwide, and has been associated with adverse birth outcomes. However, no data on CC in the Democratic Republic of the Congo are available. We investigated the prevalence, Candida species, clinical correlates, risk factors and pregnancy outcomes in women with CC in the second trimester of pregnancy.

Material and methods

In Bukavu, the Democratic Republic of the Congo, pregnant women were recruited during antenatal care between 16 and 20 weeks of gestation from January 2017 to October 2017 and followed until delivery. Sociodemographics, sexual behavioral, hygienic and clinical characteristics, microbiological data and pregnancy outcomes were collected. Candida detection and speciation was performed with microscopy (Gram-stained smears and wet-mount) and/or quantitative PCR. Multivariate regression models were used to estimate the different associations with CC.

Results

The prevalence of CC by wet mount, microscopy of Gram-stain smears and qPCR was 27.9%, 28.1% and 38.2%, respectively. C. albicans was the most prevalent Candida species (91.0%). Previous genital infections, an intermediate vaginal microbiota, bacterial vaginosis, and the use of pit toilets were risk factors for CC. Clinically, CC was associated with itching only. Women with CC had twice the odds for preterm birth, if Candida concentration was high, the odds were four times higher.

Conclusions

In Bukavu, the Democratic Republic of the Congo, the prevalence of CC was high and associated with microbiological and modifiable risk factors. Screening and treatment for CC during antenatal care should be investigated as a possible strategy to reduce preterm birth.

A rapid molecular diagnostic tool to discriminate alleles of avirulence genes and haplotypes of Phytophthora sojae using high-resolution melting analysis

Effectors encoded by avirulence genes (Avr) interact with the Phytophthora sojae resistance gene (Rps) products to generate incompatible interactions. The virulence profile of P. sojae is rapidly evolving as a result of the large-scale deployment of Rps genes in soybean. For a successful exploitation of Rps genes, it is recommended that soybean growers use cultivars containing the Rps genes corresponding to Avr genes present in P. sojae populations present in their fields. Determination of the virulence profile of P. sojae isolates is critical for the selection of soybean cultivars. High-resolution melting curve (HRM) analysis is a powerful tool, first applied in medicine, for detecting mutations with potential applications in different biological fields. Here, we report the development of an HRM protocol, as an original approach to discriminate effectors, to differentiate P. sojae haplotypes for six Avr genes. An HRM assay was performed on 24 P. sojae isolates with different haplotypes collected from soybean fields across Canada. The results clearly confirmed that the HRM assay discriminated different virulence genotypes. Moreover, the HRM assay was able to differentiate multiple haplotypes representing small allelic variations. HRM-based prediction was validated by phenotyping assays. This HRM assay provides a unique, cost-effective and efficient tool to predict virulence pathotypes associated with six different Avr (1b, 1c, 1d, 1k, 3a and 6) genes from P. sojae, which can be applied in the deployment of appropriate Rps genes in soybean fields.

Development of a high-resolution melt-based assay to rapidly detect the azole-resistant Candida auris isolates

Background and Purpose

Candida auris is a multidrug-resistant yeast that rapidly spreads, making it the leading Candidate for the next pandemic. One main leading cause of emerging resistant C. auris isolates is nonsynonymous mutations. This study aimed to detect the Y132F mutation, one of the most important azole resistance-associated mutations in the ERG-11 gene of C. auris, by developing a reliable high-resolution melt (HRM)-based method.

Materials and Methods

Five C. auris isolates from Iran, plus three control isolates from other Clades were used in the study. The antifungal susceptibility testing through micro broth dilution was performed to recheck their susceptibility to three azole antifungals, including fluconazole, itraconazole, and voriconazole. Moreover, the polymerase chain reaction (PCR) sequencing of the ERG-11 gene was performed. Following the bioinformatic analysis and HRM-specific primer design, an HRM-based assay was developed and evaluated to detect ERG-11 mutations.

Results

The minimum inhibitory concentrations of fluconazole among Iranian C. auris isolates ranged from 8 to 64 μg/mL. The PCR-sequencing of the ERG-11 gene and bioinformatic analyses revealed the mutation of Y132F, a substitution consequence of A to T on codon 395 in one fluconazole-resistant isolate (IFRC4050). The developed HRM assay successfully differentiated the targeted single nucleotide polymorphism between mutant and wild types (temperature [Tm]: 81.79 ℃ - cycle threshold [CT]: 20.06 for suspected isolate). For both mutant and non-mutant isolates, the mean Tm range was 81.79-82.39 °C and the mean CT value was 20.06-22.93. These results were completely in accordance with the findings of DNA sequencing.

Conclusion

The fast-track HRM-based method successfully detected one of the most common mechanisms of resistance in the ERG-11 gene of C. auris within 3 h. Finally, the development of more panels of HRM assays for the detection of all azole resistance mutations in C. auris ERG-11 is recommended to expand the scope of the field and facilitate the elaboration of rapid and accurate methods of antifungal resistance assessment.

Silver Nanoparticles: A Promising Antifungal Agent against the Growth and Biofilm Formation of the Emergent Candida auris

Candida auris is a globally-emerging pathogen that is correlated to nosocomial infections and high mortality rates, causing major outbreaks in hospitals and serious public health concerns worldwide. This study investigated the antifungal activity of silver nanoparticles (AgNPs) on clinical isolates of C. auris. A total of eight clinical isolates were collected from blood, urine, ear swab, and groin. C. auris was confirmed by MALDI-TOF MS, and gene sequencing. All isolates confirmed as C. auris were subjected to antimicrobial agents, including amphotericin B, fluconazole, caspofungin, voriconazole, micafungin, and flucytosine. A serial dilution of a silver nanoparticles solution was prepared to test antifungal susceptibility testing under planktonic conditions. Moreover, an antibiofilm activity assay was determined using a colony-forming assay and a cell viability assay by a live−dead yeast kit. Significant antifungal and antibiofilm activity of AgNPs was detected against all isolates; MIC was <6.25 μg/mL, the range of MFC was from 6.25 to 12.5 μg/mL for all isolates, and the highest value of IC50 was 3.2 μg/mL. Silver nanomaterials could represent a possible antimicrobial agent to prevent outbreaks caused by C. auris infections.

Convolutional neural network analysis of recurrence plots for high resolution melting classification

BACKGROUND AND OBJECTIVE

High resolution melting (HRM) analysis is a rapid and correct method for identification of species, such as, microorganism, bacteria, yeast, virus, etc. HRM data are produced using real-time polymerase chain reaction (PCR) and unique for each species. Analysis of the HRM data is important for several applications, such as, for detection of diseases (e.g., influenza, zika virus, SARS-Cov-2 and Covid-19 diseases) in health, for identification of spoiled foods in food industry, for analysis of crime scene evidence in forensic investigation, etc. However, the characteristics of the HRM data can change due to the experimental conditions or instrumental settings. In addition, it becomes laborious and time-consuming process as the number of samples increases. Because of these reasons, the analysis and classification of the HRM data become challenging for species which have similar characteristics.

METHODS

To improve the classification accuracy of HRM data, we propose to use image (visual) representation of HRM data, which we call HRM images, that are generated using recurrence plots, and propose convolutional neural network (CNN) based models for classifying HRM images. In this study, two different types of recurrence plots are generated, which are black-white recurrence plots (BW-RP) and gray scale recurrence plots (GS-RP) and four different CNN models are proposed for classifying HRM data.

RESULTS

The classification performance of the proposed methods are evaluated based on average classification accuracy and F1 score, specificity, recall, and precision values for each yeast species. When BW-RP representation of HRM data is used as input to the CNN models, the best classification accuracy of 95.2% is obtained. The classification accuracies of CNN models for melting curve and GS-RP data representations of HRM data are 90.13% and 86.13%, respectively. The classification accuracy of support vector machines (SVM) model that take melting curve representation of HRM data is 86.53%. Moreover, when BW-RP representation of HRM data is used as input to the CNN models, the F1 score, specificity, recall and precision values are the highest for almost all of species.

CONCLUSIONS

Experimental results show that using BW-RP representation of HRM data improved the classification accuracy of HRM data and CNN models that take these images as input outperformed CNN models that take melting curve and GS-RP representations of HRM data as inputs and SVM model that take melting curve representation of HRM data as input.

Comparison of High-resolution Melting Curve Analysis with Specific Target Gene Sequencing to Identify the Most Common Species of Aspergillus and Fusarium

Background: Currently, it appears that new molecular-based methods could substitute microscopic and culture assessment for the first-line detection of microorganisms isolated from clinical specimens. However, it will remain the "continual strategy" until this technology is attuned to identifying all fungi that can be isolated from biological specimens. Objectives: The present study aimed to validate a high-resolution melting (HRM) technique to identify clinical filamentous fungi. Moreover, it was attempted to compare the results with those of the target gene’s polymerase chain reaction (PCR) sequencing. Methods: A total of 54 specimens of bronchoalveolar lavage (BAL), nail, ear discharge, blood culture, and cornea were collected from patients suspected of fungal infection. All Fusarium spp. and Aspergillus spp. were recognized based on Tef-α and beta-tubulin region sequencing, as well as PCR-HRM analysis. Results: The Tef-α sequence analysis revealed the most frequent spp. to be Fusarium solani followed by F. oxysporum (n = 3), F. caucasicum (n = 3), F. coeruleum (n = 3), F. falciforme (n = 1), F. proliferatum (n = 1), F. brevicatenulatum (n = 1), F. globosom (n = 1), and F. verticillioides (n = 1). Based on the beta-tubulin sequences, Aspergillus flavus (n = 10), A. fumigatus (n = 7), A. niger (n = 2), A. terreus (n = 1), and A. orezea (n = 1) were identified in this study. Furthermore, the dataset analysis of PCR-HRM revealed that 33 isolates belonging to Fusarium spp. were F. solani (n = 24), F. oxysporum (n = 3), F. proliferatum (n = 3), F. falciforme (n = 1), F. verticillioides (n = 1), and F. brevicatenulatum (n = 1). Moreover, isolates (n = 21) belonging to Aspergillus spp. included A. flavus (n = 11), A. fumigatus (n = 7), A. niger (n = 2), and A. terreus (n = 1). Conclusions: The sequencing method has a time-consuming and costly nature, and there exists conformity between the sequence results of the Tef-α/beta-tubulin regions and PCR-HRM. The PCR-HRM method is a reliable approach in the clinical laboratory to identify Aspergillus and Fusarium spp. However, some closely related spp. show no curve algorithm differences in PCR-HRM.

Drug Resistance-Associated Mutations in ERG11 of Multidrug-Resistant Candida auris in a Tertiary Care Hospital of Eastern Saudi Arabia

Candida auris is an emerging multi-drug resistant pathogen with high mortality rate; nosocomial infections have been reported worldwide, causing a major challenge for clinicians and microbiological laboratories. The study aims to describe new cases of C. auris and detect drug resistance-associated mutations of C. auris by the sequencing of ERG11 and FKS1 genes. A total of six specimens were collected from blood, urine, ear swab, and groin screening samples. Isolates were incubated for 48 h on Sabouraud Dextrose agar (SDA) at 42 °C, then confirmed by MALDI-TOF MS. Furthermore, antifungal susceptibility testing was performed using the Vitek 2 system to detect Minimum Inhibitory Concentrations (MICs) of six antifungals. Sequences of 18S rRNA gene and ITS regions from isolates and phylogenetic analysis were performed. Gene sequencing was analysed to detect drug resistance-associated mutations by FKS1 and ERG11 genes sequencing. All C. auris isolates were confirmed by MALDI-TOF MS, and evolutionary analyses using sequences of 18S rRNA gene and ITS region. Antifungal susceptibility testing showed that all isolates were resistant to fluconazole. Sequencing of ERG11 and FKS1 genes from the isolates revealed the presence of two (F132Y and K143R) drug resistance-associated mutations in ERG11, however, FKS1 gene was devoid of mutations. The study sheds light on a public health threat of an emerging pathogen, and the hospital implemented strict contact screening and infection control precautions to prevent C. auris infection. Finally, there is a critical need to monitor the antifungal resistance in different geographical areas and implementation of efficient guidelines for treatment.

Molecular identification of Candida isolates by Real-time PCR-high-resolution melting analysis and investigation of the genetic diversity of Candida species

BACKGROUND

Candida species are considered as the cause of one of the most important opportunistic fungal diseases. Accurate identification of Candida species is important because of antifungal susceptibility patterns are different among these species, so proper identification helps in the selection of antifungal drugs for the prevention and treatment. Phenotypic methods for identification of Candida species, which are widely used in clinical microbiology laboratories, have some limitations. Real-time PCR followed by the high-resolution melting analysis (HRMA) is a novel approach for the rapid recognition of pathogenic fungi. Molecular phylogeny is essential for obtaining a better understanding of the evolution of the genus Candida and the identification of the relative degree of the Candida species. The purpose of this study was molecular identification of Candida isolates by Real-time PCR-high-resolution melting analysis and investigation of the genetic diversity of Candida species.

METHODS

Two hundred and thirty-two Candida isolates including 111 Candida isolates obtained from 96 HIV/AIDS patients and 121 Candida isolates obtained from 98 non-HIV persons were identified by real-time PCR and high-resolution melting curve analysis. To evaluate genetic diversity and relationships among Candida species, PCR products of nine clinical Candida isolates, as a representative of each kind of species, were randomly selected for DNA sequence analysis.

RESULTS

In HIV/AIDS patients, six species of Candida spp. were identified as follows: C albicans (n = 64; 57.7%), C glabrata (n = 31; 27.92%), C parapsilosis (n = 9; 8.1%), C tropicalis (n = 4; 3.6%), C krusei (n = 2; 1.8%), and C kefyr (n = 1; 0.90%). In non-HIV persons, we identified eight species of Candida including C albicans (n = 46; 38.33%) followed by C glabrata and C krusei (each one, n = 18; 15%), C tropicalis (n = 13; 10.83%), C lusitaniae (n = 12; 5.17%), C parapsilosis (n = 10; 4.31%), and C kefyr and C guillermondii (each one, n = 2; 1.66%). Also, the phylogenetic analysis showed the presence of two main clades and six separate subclades. Accordingly, about 88.9% of the isolates were located in clade I and 11.10% of the studied isolates were in clade II.

CONCLUSIONS

Real-time PCR followed by high-resolution melting analysis (HRMA) is known as a reliable, fast, and simple approach for detection and accurate identification of Candida species, especially in clinical samples.

Recent trends in molecular diagnostics of yeast infections: from PCR to NGS

The incidence of opportunistic yeast infections in humans has been increasing over recent years. These infections are difficult to treat and diagnose, in part due to the large number and broad diversity of species that can underlie the infection. In addition, resistance to one or several antifungal drugs in infecting strains is increasingly being reported, severely limiting therapeutic options and showcasing the need for rapid detection of the infecting agent and its drug susceptibility profile. Current methods for species and resistance identification lack satisfactory sensitivity and specificity, and often require prior culturing of the infecting agent, which delays diagnosis. Recently developed high-throughput technologies such as next generation sequencing or proteomics are opening completely new avenues for more sensitive, accurate and fast diagnosis of yeast pathogens. These approaches are the focus of intensive research, but translation into the clinics requires overcoming important challenges. In this review, we provide an overview of existing and recently emerged approaches that can be used in the identification of yeast pathogens and their drug resistance profiles. Throughout the text we highlight the advantages and disadvantages of each methodology and discuss the most promising developments in their path from bench to bedside.

Comparison of the efficiency of different cell lysis methods and different commercial methods for RNA extraction from Candida albicans stored in RNAlater

BACKGROUND

Obtaining sufficient RNA yield and quality for comprehensive transcriptomic studies is cumbersome for clinical samples in which RNA from the pathogen is present in low numbers relative to the nucleic acids from the host, especially for pathogens, such as yeasts, with a solid cell wall. Therefore, yeast cell lysis including cell wall disruption constitutes an essential first step to maximize RNA yield. Moreover, during the last years, different methods for RNA extraction from yeasts have been developed, ranging from classic hot phenol methods to commercially available specific kits. They offer different RNA yield and quality, also depending on the original storage medium, such as RNAlater.

RESULTS

We observed that, for C. albicans cells stored in Tryptic Soy Broth with 15% glycerol, 10 min of bead beating in a horizontal position in RiboPure Lysis Buffer provided complete cell lysis. Cell lysis efficiency was decreased to 73.5% when cells were stored in RNAlater. In addition, the RiboPure Yeast Kit (Ambion) offered the highest RNA yield in comparison with the automated platform NucliSENS easyMAG total nucleic extraction (bioMérieux) and the RNeasy Mini Kit (Qiagen) according to NanoDrop and Fragment Analyzer. Moreover, we showed that, in spite of the decrease of cell lysis efficiency after RNAlater storage, as compared to storage in TSB + 15% glycerol, RNAlater increased RNA yield during RNA extraction with both RiboPure Yeast Kit and easyMAG, as confirmed by Fragment Analyzer analysis and by RT-qPCR of the RNA from the Internal Transcribed Spacer 2.

CONCLUSIONS

In our hands, the most efficient cell lysis and highest RNA yield from C. albicans cells stored in RNAlater was obtained by horizontal bead beating in RiboPure Lysis Buffer followed by RNA extraction with the RiboPure Yeast Kit.

Urogenital pathogens, associated with Trichomonas vaginalis, among pregnant women in Kilifi, Kenya: a nested case-control study

Background

Screening of curable sexually transmitted infections is frequently oriented towards the diagnosis of chlamydia, gonorrhea, syphilis and trichomoniasis, whereas other pathogens, sometimes associated with similar urogenital syndromes, remain undiagnosed and/or untreated. Some of these pathogens are associated with adverse pregnancy outcomes.

Methods

In a nested case-control study, vaginal swabs from 79 pregnant women, i.e., 28 T. vaginalis-positive (cases) and 51 T. vaginalis-negative (controls), were screened by quantitative PCR for Adenovirus 1 and 2, Cytomegalovirus, Herpes Simplex Virus 1 and 2, Chlamydia trachomatis, Escherichia coli, Haemophilus ducreyi, Mycoplasma genitalium, M. hominis, candidatus M. girerdii, Neisseria gonorrhoeae, Streptococcus agalactiae, Treponema pallidum, Ureaplasma parvum, U. urealyticum, and Candida albicans. Additionally, we determined whether women with pathogens highly associated with T. vaginalis had distinct clinical signs and symptoms compared to women with T. vaginalis mono-infection.

Results

M. hominis was independently associated with T. vaginalis (adjusted odds ratio = 6.8, 95% CI: 2.3–19.8). Moreover, M. genitalium and Ca M. girerdii were exclusively detected in women with T. vaginalis (P = 0.002 and P = 0.001), respectively. Four of the six women co-infected with T. vaginalis and Ca M. girerdii complained of vaginal itching, compared to only 4 out of the 22 women infected with T. vaginalis without Ca M. girerdii (P = 0.020).

Conclusion

We confirm M. hominis as a correlate of T. vaginalis in our population, and the exclusive association of both M. genitalium and Ca. M. girerdii with T. vaginalis. Screening and treatment of these pathogens should be considered.

Electronic supplementary material

The online version of this article (10.1186/s12879-018-3455-4) contains supplementary material, which is available to authorized users.

Clinically relevant yeast species identified by sequencing the internal transcribed spacer region of r-RNA gene and Vitek 2 compact (YST card) commercial identification system: Experience in a Tertiary Care Hospital in Assam, Northeast India

In this retrospective study from 2012 to 2015, 333 clinical isolates of yeasts were identified using Vitek 2 Compact System YST ID card (Biomerieux, France) and internal transcribed spacer (ITS) sequencing. Eighteen species were identified by ITS sequencing. Candida albicans was the most common species (46.5%), followed by Candida tropicalis (27%). The total species supported by Vitek System was 11 (61.11%). The sensitivity of the system in identifying these 11 species was 66.66%-100%; specificity 98.37%-100%; positive predictive value 70%-100%, negative predictive value 96.05%-100%, and diagnostic accuracy 96.99%-100%. Diagnostic accuracy of ITS1 and ITS2 sequences individually was 98.49% and 100% using NCBI Genbank database.

Rapid detection of fungal pathogens in bronchoalveolar lavage samples using panfungal PCR combined with high resolution melting analysis

Despite advances in the treatment of invasive fungal diseases (IFD), mortality rates remain high. Moreover, due to the expanding spectrum of causative agents, fast and accurate pathogen identification is necessary. We designed a panfungal polymerase chain reaction (PCR), which targets the highly variable ITS2 region of rDNA genes and uses high resolution melting analysis (HRM) for subsequent species identification. The sensitivity and specificity of this method was tested on a broad spectrum of the most clinically important fungal pathogens including Aspergillus spp., Candida spp. and mucormycetes. Despite the fact that fluid from bronchoalveolar lavage (BAL) is one of the most frequently tested materials there is a lack of literature sources aimed at panfungal PCR as an IFD diagnostic tool from BAL samples. The applicability of this method in routine practice was evaluated on 104 BAL samples from immunocompromised patients. Due to high ITS region variability, we obtained divergent melting peaks for different fungal species. Thirteen out of 18 patients with proven or probable IFD were positive. Therefore, the sensitivity, specificity, positive predictive value and negative predictive value of our method were 67%, 100%, 100%, and 94%, respectively. In our assay, fungal pathogens identification is based on HRM, therefore omitting the expensive and time consuming sequencing step. With the high specificity, positive and negative predictive values, short time needed to obtain a result, and low price, the presented assay is intended to be used as a quick screening method for patients at risk of IFD.

The Potential Power of Bar-HRM Technology in Herbal Medicine Identification

The substitution of low-cost or adulterated herbal products for high-priced herbs makes it important to be able to identify and trace herbal plant species and their processed products in the drug supply chain. PCR-based methods play an increasing role in monitoring the safety of herbal medicines by detecting adulteration. Recent studies have shown the potential of DNA barcoding combined with high resolution melting (Bar-HRM) analysis in herbal medicine identification. This method involves precisely monitoring the change in fluorescence caused by the release of an intercalating DNA dye from a DNA duplex as it is denatured by a gradual increase in temperature. Since the melting profile depends on the GC content, length, and strand complementarity of the amplification product, Bar-HRM analysis opens up the possibility of detecting single-base variants or species-specific differences in a short region of DNA. This review summarizes key factors affecting Bar-HRM analysis and describes how Bar-HRM is performed. We then discuss advances in Bar-HRM analysis of medicinal plant ingredients (herbal materia medica) as a contribution toward safe and effective herbal medicines.