Martina Šeruga Musić

The use of SSCP analysis in the assessment of phytoplasma gene variability

Single-strand conformation polymorphism (SSCP) analysis is a broadly used technique for detecting mutations. The aim of this work was to assess the applicability of SSCP as a new tool for the detection of the molecular variability of uncultivable mollicutes - phytoplasmas. Three phytoplasma regions were investigated: 16S rDNA, tuf gene, and dnaB gene. Fragments amplified by PCR were subjected to SSCP under conditions optimized for each fragment length. In all of the analyzed regions, SSCP revealed the presence of polymorphism undetected by routine RFLP analyses. Reliability of the method was confirmed by the multiple alignments and phylogenetic analyses of representative sequences showing different SSCP profiles.

A case study of FD and BN phytoplasma variability in Croatia: multigene sequence analysis approach

Uncultivable bacteria from the genus ‘Candidatus Phytoplasma’ are associated with grapevine yellows (GY) diseases worldwide. In Euro-Mediterranean viticultural areas, GY are most frequently caused by Bois Noir (BN) and Flavescence Dorée (FD) phytoplasmas. Surveys of GY in Croatia have been conducted regularly since 1997. BN phytoplasmas have been found to be widespread, while FD phytoplasmas were recently discovered in restricted areas of the country. The aim of this study was to assess the variability of genotypes involved in GY pathosystems by a multilocus sequence typing (MLST) approach. Grapevine, weed and insect vector samples were collected from three locations. Species-specific stamp and vmp1 genes, together with house-keeping genes tuf and secY, were amplified from BN strains. In FD strains, the genes secY, map and uvrB-degV were analyzed. MLST revealed a diversity of BN genotypes, one of which was prevalent and identified in samples of grapevine and the insect vector Hyalesthes obsoletus, corroborating their affiliation to the same pathosystem. Distinct BN strains found in bindweed and two grapevine samples indicated the presence of different BN pathosystems involving a yet unidentified vector, possibly from the genus Reptalus. Moreover, a co-occurence of BN and FD phytoplasma in the same vineyard was identified. The genotyping of FD strains from both grapevine and Scaphoideus titanus showed the presence of at least two distinct FD genotypes at two different locations, suggesting separate introductions of the disease into the country. In this study, MLST proved to be a useful and informative tool in advancing the understanding of GY epidemiology in Croatia.

Pan Drug-Resistant Environmental Isolate of Acinetobacter baumannii from Croatia

Acinetobacter baumannii is an emerging nosocomial pathogen with also emerging resistance to different antibiotics. Multidrug and pan drug-resistant clinical isolates were reported worldwide. Here we report the first evidence of pan drug-resistant environmental isolate of A. baumannii. The isolate was recovered from the effluent of secondary treated municipal wastewater of the City of Zagreb, Croatia. The isolate was resistant to penicillins/β-lactamase inhibitors, carbapenems, fluoroquinolones, aminoglycosides, folate pathway inhibitors, and polymyxins, except intermediately susceptible to minocycline and tigecycline. Intrinsic chromosomally located blaOXA-51-like gene and acquired plasmid-located blaOXA-23-like gene were related to clinical isolates. Pan drug-resistant A. baumannii can occur in natural environments outside of the hospital. Secondary treated municipal wastewater represents a potential epidemiological reservoir of pan drug-resistant A. baumannii and carbapenem resistance gene.

Extensively and multi drug-resistant Acinetobacter baumannii recovered from technosol at a dump site in Croatia

In a karst pit above City of Rijeka in Croatia the hazardous industrial waste was continuously disposed from 1955 to 1990, and later it was periodically used as an illegal dump site. The surface part of a technosol at the edge of dump was analysed mineralogically, geochemically and bacteriologically. From the technosol rich in petroleum hydrocarbons and heavy metals three isolates of Acinetobacter baumannii were recovered. Isolates from technosol shared many features that are previously described for clinically isolates: the affiliation to IC1 and 2, multi-drug resistant (MDR) or extensively drug-resistant (XDR) antibiotic resistance profile, carbapenem resistance mediated by blaOXA72 and blaOXA23 genes, and the expression of virulence factors. In in vitro conditions, isolates were able to survive in contact with technosol during 58days of monitoring. The most probable source of A. baumannii in technosol was the illegally disposed hospital waste. Proper management and disposal of human solid waste is mandatory to prevent the spread of clinically important A. baumannii in nature.

Single-Strand Conformation Polymorphism Analysis for Differentiating Phytoplasma Strains

Single-strand conformation polymorphism (SSCP) analysis is a sensitive and rapid technique for detecting DNA polymorphisms and mutations in PCR-amplified fragments. Due to its technical simplicity, it is widely used as a screening tool in various investigations, ranging from clinical diagnosis of human hereditary diseases to the characterization of microbial communities. This method can also be used successfully on phytoplasmas as a tool for the detection of molecular variability in conserved housekeeping genes such as 16S rRNA and tuf, as well as in more variable genes, revealing the presence of polymorphisms undetected by routine RFLP analyses. The reliability of SSCP has been confirmed by multiple alignments and phylogenetic analyses of representative sequences showing different SSCP profiles. However, it is not broadly applied in phytoplasma research yet. The technique provides an inexpensive, convenient, and sensitive method for determining sequence variation and to differentiate phytoplasma strains, and is particularly suitable for epidemiological studies or as a fast screening, typing tool when dealing with a large number of field samples.