Analysis of strain relatedness using high resolution melting in a case of recurrent candiduria

Characterization of Actinobacterial Strains as Potential Biocontrol Agents against Macrophomina phaseolina and Rhizoctonia solani, the Main Soil-Borne Pathogens of Phaseolus vulgaris in Cuba

Macrophomina phaseolina and Rhizoctonia solani are considered two major soil-borne pathogens of Phaseolus vulgaris in Cuba. Their management is difficult, not only due to their intrinsic biology as soil-borne pathogens, but also because the lack of active ingredients available against these pathogens. Actinobacteria, a heterogeneous bacterial group traditionally known as actinomycetes have been reported as promising biological control agents (BCAs) in crop protection. Thus, the main objective of this study was to evaluate the effectiveness of 60 actinobacterial strains as BCAs against M. phaseolina and R. solani in vitro by dual culture assays. The most effective strains were characterized according to their cellulolytic, chitinolytic and proteolytic extracellular enzymatic activity, as well as by their morphological and biochemical characters in vitro. Forty and 25 out of the 60 actinobacteria strains inhibited the mycelial growth of M. phaseolina and R. solani, respectively, and 18 of them showed a common effect against both pathogens. Significant differences were observed on their enzymatic and biochemical activity. The morphological and biochemical characters allow us to identify all our strains as species belonging to the genus Streptomyces. Streptomyces strains CBQ-EA-2 and CBQ-B-8 showed the highest effectiveness in vitro. Finally, the effect of seed treatments by both strains was also evaluated against M. phaseolina and R. solani infections in P. vulgaris cv. Quivicán seedlings. Treatments combining the two Streptomyces strains (CBQ-EA-2 + CBQ-B-8) were able to reduce significantly the disease severity for both pathogen infections in comparison with the non-treated and inoculated control. Moreover, they showed similar effect than that observed for Trichoderma harzianum A-34 and with Celest® Top 312 FS (Syngenta®; Basilea, Switzerland) treatments, which were included for comparative purposes.

Genotypic diversity and antifungal susceptibility pattern of Candida albicans species isolated from hospitalized paediatric patients with urinary tract infection in Iran

AIMS

The present study aimed to determine the microsatellite length polymorphism (MLP) genotypic patterns and antifungal susceptibility profiles of Candida albicans isolated from patients with candiduria.

METHODS AND RESULTS

DNA of 50 C. albicans isolates was used for molecular identification based on the ITS₁ -5.8s-ITS₂ region. MLP assays were performed to amplify three loci (EF3, CDC3 and HIS3), and PCR products were used for fragment analysis. Antifungal susceptibility tests were performed according to CLSI M27 4th ed guidelines. In all, 38 different genotypes were detected with the three polymorphic loci among C. albicans isolates, and only one genotype was homozygous. In comparison to other countries, our genotypes were divided into three clusters, two of which were linked to France and a third of which was linked to Austria. The genetic structures of the 50 C. albicans isolates revealed varied heterozygosity and significant Hardy-Weinberg equilibrium at the EF3 locus. Only one (2%) and four (8%) of isolates showed resistance to fluconazole and itraconazole, respectively. In C. albicans genotype G25, one (2%) of the isolates showed cross-resistance and non-wild-type resistance to posaconazole, itraconazole and fluconazole.

CONCLUSION

MLP typing is a useful tool to analyse the genetic structure of C. albicans isolates. High genetic diversity (38 genotypes) was detected in the isolates tested here. Compared to isolates in other countries, the ones from our patients had a clear relationship with French and Austrian isolates.

SIGNIFICANCE AND IMPACT OF THE STUDY

Iranian isolates of C. albicans have a distinct genotype and show similarities only with French and Austrian isolates.

Dynamic time warping assessment of high-resolution melt curves provides a robust metric for fungal identification

Fungal infections are a global problem imposing considerable disease burden. One of the unmet needs in addressing these infections is rapid, sensitive diagnostics. A promising molecular diagnostic approach is high-resolution melt analysis (HRM). However, there has been little effort in leveraging HRM data for automated, objective identification of fungal species. The purpose of these studies was to assess the utility of distance methods developed for comparison of time series data to classify HRM curves as a means of fungal species identification. Dynamic time warping (DTW), first introduced in the context of speech recognition to identify temporal distortion of similar sounds, is an elastic distance measure that has been successfully applied to a wide range of time series data. Comparison of HRM curves of the rDNA internal transcribed spacer (ITS) region from 51 strains of 18 fungal species using DTW distances allowed accurate classification and clustering of all 51 strains. The utility of DTW distances for species identification was demonstrated by matching HRM curves from 243 previously identified clinical isolates against a database of curves from standard reference strains. The results revealed a number of prior misclassifications, discriminated species that are not resolved by routine phenotypic tests, and accurately identified all 243 test strains. In addition to DTW, several other distance functions, Edit Distance on Real sequence (EDR) and Shape-based Distance (SBD), showed promise. It is concluded that DTW-based distances provide a useful metric for the automated identification of fungi based on HRM curves of the ITS region and that this provides the foundation for a robust and automatable method applicable to the clinical setting.

Capillary electrophoresis based on nucleic acid detection for diagnosing human infectious disease

Rapid transmission, high morbidity, and mortality are the features of human infectious diseases caused by microorganisms, such as bacteria, fungi, and viruses. These diseases may lead within a short period of time to great personal and property losses, especially in regions where sanitation is poor. Thus, rapid diagnoses are vital for the prevention and therapeutic intervention of human infectious diseases. Several conventional methods are often used to diagnose infectious diseases, e.g. methods based on cultures or morphology, or biochemical tests based on metabonomics. Although traditional methods are considered gold standards and are used most frequently, they are laborious, time consuming, and tedious and cannot meet the demand for rapid diagnoses. Disease diagnosis using capillary electrophoresis methods has the advantages of high efficiency, high throughput, and high speed, and coupled with the different nucleic acid detection strategies overcomes the drawbacks of traditional identification methods, precluding many types of false positive and negative results. Therefore, this review focuses on the application of capillary electrophoresis based on nucleic detection to the diagnosis of human infectious diseases, and offers an introduction to the limitations, advantages, and future developments of this approach.

Antimicrobial peptide CRAMP (16-33) stalls bacterial cytokinesis by inhibiting FtsZ assembly

A cathelin-related antimicrobial peptide (CRAMP) of 37 amino acid residues is thought to regulate innate immunity and provide a host defense mechanism in mammals. Here, a part of the CRAMP peptide, CRAMP (16-33) (GEKLKKIGQKIKNFFQKL), was found to bind to FtsZ and to inhibit the assembly and GTPase activity of FtsZ in vitro. A computational analysis indicated that CRAMP (16-33) binds in the cavity of the T7 loop of FtsZ. Both hydrophobic and ionic interactions were involved in the binding interactions. Further, CRAMP (16-33) inhibited the formation of the FtsZ ring in bacteria, indicating that it inhibited bacterial cell division by inhibiting FtsZ assembly.

Molecular fingerprints to identify Candida species

A wide range of molecular techniques have been developed for genotyping Candida species. Among them, multilocus sequence typing (MLST) and microsatellite length polymorphisms (MLP) analysis have recently emerged. MLST relies on DNA sequences of internal regions of various independent housekeeping genes, while MLP identifies microsatellite instability. Both methods generate unambiguous and highly reproducible data. Here, we review the results achieved by using these two techniques and also provide a brief overview of a new method based on high-resolution DNA melting (HRM). This method identifies sequence differences by subtle deviations in sample melting profiles in the presence of saturating fluorescent DNA binding dyes.