Large-Scale Biogeographical Shifts of Abundance of Antibiotic Resistance Genes and Marine Bacterial Communities as Their Carriers along a Trophic Gradient.

The role of marine environments in the global spread of antibiotic resistance still remains poorly understood, leaving gaps in the One Health-based research framework. Antibiotic resistance genes (ARGs) encoding resistance to five major antibiotic classes, including sulfonamides (sul1, sul2), tetracyclines (tetA, tetB), ß-lactams (blaCTX-M, blaTEMblaVIM), macrolides (ermB, mphA), aminoglycosides (aac3-2), and integrase gene (intl1) were quantified by RT-qPCR, and their distribution was investigated in relation to environmental parameters and the total bacterial community in bottom layer and surface waters of the central Adriatic (Mediterranean), over a 68 km line from the wastewater-impacted estuary to coastal and pristine open sea. Seasonal changes (higher in winter) were observed for antibiotic resistance frequency and the relative abundances of ARGs, which were generally higher in eutrophic coastal areas. In particular, intl1, followed by blaTEM and blaVIM, were strongly associated with anthropogenic influence and Gammaproteobacteria as their predominant carriers. Water column stratification and geographic location had a significant influence on ARGs distribution in the oligotrophic zone, where the bacterial community exhibited a seasonal shift from Gammaproteobacteria in winter to Marine group II in summer.

Marine resistome of a temperate zone: Distribution, diversity, and driving factors across the trophic gradient.

Marine and ocean environments are the most widespread habitats in the world but are still the least studied from the aspect of antibiotic resistance. The indigenous and tetracycline (TET)- and sulfamethoxazole (SXT)-resistant planktonic bacterial communities were simultaneously investigated for the first time along a trophic gradient of a temperate zone, regarding their taxonomic and functional structures as well as biotic and abiotic factors affecting their dynamics as vehicles of antibiotic resistance genes (ARGs), thus impacting the ARGs distribution at seasonal and spatial scales. A total of 80 microbiomes, recovered seasonally from bottom layer and surface waters along a 68-km transect from wastewater-impacted estuary to coastal and pristine open sea in the central Adriatic (Mediterranean Sea), were analysed using 16S rRNA amplicon sequencing, PICRUSt2 bioinformatics and extensive biostatistics. Eighty-one bacterial phyla were identified, with majority (n = 49) in summer when communities were found to be more species enriched across the gradient. Microbial diversity was more site-specific and pronounced in surface microbiomes in winter. Nevertheless, both richness and community diversity decreased with distance from the coast. Although the microbiomes from human-influenced sites significantly differed from those in oligotrophic offshore area, Proteobacteria were still the most abundant phylum during both seasons at the surface and seabed along the gradient, and the major contributors to the marine resistome regarding native and TET- and SXT-resistant microbial communities. Resistome structure was more diverse in winter, whereas peptide, vancomycin and multidrug resistance modules predominated regardless of season, trophic status, or antibiotic. However, multidrug, beta-lactam resistance modules as well as macrolide, phenicol, aminoglycoside, and particularly imipenem resistance genes were much more frequent in winter, suggesting that the diversity of indigenous resistomes is highly dependent on seasonal variations of the water column, driven by thermohaline stratification and nutrients. Moreover, several pathogenic genera stood out as important carriers of multiple resistance traits in TET- and SXT-related resistomes in both seasons, particularly Acinetobacter, Vibrio, Bacillus and Pseudomonas, beside which Proteus, Serratia and Bacteroides prevailed in native resistomes. This study evidenced seasonal and spatial variations of the marine microbiome and resistome and their driving forces along the trophic gradient, providing a comprehensive insight into the diversity and distribution of antibiotic resistance in the marine ecosystem of a temperate zone.

Molecular Characterization and Mutational Analysis of Clarithromycin- and Levofloxacin-Resistance Genes in Helicobacter pylori from Gastric Biopsies in Southern Croatia.

Point mutations in the 23S rRNA, gyrA, and gyrB genes can confer resistance to clarithromycin (CAM) and levofloxacin (LVX) by altering target sites or protein structure, thereby reducing the efficacy of standard antibiotics in the treatment of Helicobacter pylori infections. Considering the confirmed primary CAM and LVX resistance in H. pylori infected patients from southern Croatia, we performed a molecular genetic analysis of three target genes (23S rRNA, gyrA, and gyrB) by PCR and sequencing, together with computational molecular docking analysis. In the CAM-resistant isolates, the mutation sites in the 23S rRNA gene were A2142C, A2142G, and A2143G. In addition, the mutations D91G and D91N in GyrA and N481E and R484K in GyrB were associated with resistance to LVX. Molecular docking analyses revealed that mutant H. pylori strains with resistance-related mutations exhibited a lower susceptibility to CAM and LVX compared with wild-type strains due to significant differences in non-covalent interactions (e.g., hydrogen bonds, ionic interactions) leading to destabilized antibiotic-protein binding, ultimately resulting in antibiotic resistance. Dual resistance to CAM and LVX was found, indicating the successful evolution of H. pylori resistance to unrelated antimicrobials and thus an increased risk to human health.

Microbiome profiling and characterization of virulent and vancomycin-resistant Enterococcus faecium from treated and untreated wastewater, beach water and clinical sources.

Vancomycin-resistant Enterococcus faecium (VREfm) is an opportunistic pathogen among the highest global priorities regarding public and environmental health. Following One Health approach, we determined for the first time the antibiotic resistance and virulence genes, and sequence types (STs) affiliation of VREfm recovered simultaneously from marine beach waters, submarine outfall of a wastewater treatment plant and an offshore discharge of untreated sewage, and compared them with the surveillance VREfm from regional university hospital in Croatia to assess the hazard of their transmission and routes of introduction into the natural environment. Importantly, VREfm recovered from wastewater, coastal bathing waters and hospital shared similar virulence, multidrug resistance, and ST profiles, posing a major public health threat. All isolates carried the vanA gene, while one clinical isolate also possessed the vanC2/C3 gene. The hospital strains largely carried the aminoglycoside-resistance genes aac(6')-Ie-aph(2″)-Ia, and aph(2″)-Ib and aph(2″)-Id, which were also predominant in the environmental isolates. The hyl gene was the most prevalent virulence gene. The isolates belonged to 10 STs of the clonal complex CC17, a major epidemic lineage associated with hospital infections and outbreaks, with ST117 and ST889 common to waterborne and hospital isolates, pointing to their sewage-driven dissemination. To gain better insight into the diversity of accompanying taxons in the surveyed water matrices, microbiome taxonomic profiling was carried out using Illumina-based 16S rDNA sequencing and their resistome features predicted using the PICRUSt2 bioinformatics tool. An additional 60 pathogenic bacterial genera were identified, among which Arcobacter, Acinetobacter, Escherichia-Shigella, Bacteroides and Pseudomonas were the most abundant and associated with a plethora of antibiotic resistance genes and modules, providing further evidence of the hazardous effects of wastewater discharges, including the treated ones, on the natural aquatic environment that should be adequately addressed from a sanitary and technological perspective.

Metagenomic analysis of pioneer biofilm-forming marine bacteria with emphasis on Vibrio gigantis adhesion dynamics.

Marine biofilms occur frequently and spontaneously in seawater, on almost any submerged solid surface. At the early stages of colonization, it consists of bacteria and evolves into a more complex community. Using 16S rRNA amplicon sequencing and comparative metagenomics, the composition and predicted functional potential of one- to three-day old bacterial communities in surface biofilms were investigated and compared to that of seawater. This confirmed the autochthonous marine bacterium Vibrio gigantis as an early and very abundant biofilm colonizer, also functionally linked to the genes associated with cell motility, surface attachment, and communication via signaling molecules (quorum sensing), all crucial for biofilm formation. The dynamics of adhesion on a solid surface of V. gigantis alone was also monitored in controlled laboratory conditions, using a newly designed and easily implementable protocol. Resulting in a calculated percentage of bacteria-covered surface, a convincing tendency of spontaneous adhering was confirmed. From the multiple results, its quantified and reproducible adhesion dynamics will be used as a basis for future experiments involving surface modifications and coatings, with the goal of preventing adhesion.

Microbiome and antibiotic resistance profiling in submarine effluent-receiving coastal waters in Croatia.

Wastewater treatment plant (WWTP) effluents are pointed as hotspots for the introduction of both commensal and pathogenic bacteria as well as their antibiotic resistance genes (ARGs) in receiving water bodies. For the first time, the effect of partially treated submarine effluents was explored at the bottom and surface of the water column to provide a comprehensive overview of the structure of the microbiome and associated AR, and to assess environmental factors leading to their alteration. Seawater samples were collected over a 5-month period from submarine outfalls in central Adriatic Sea, Croatia. 16S rRNA amplicon sequencing was used to establish taxonomic and resistome profiles of the bacterial communities. The community differences observed between the two discharge areas, especially in the abundance of Proteobacteria and Firmicutes, could be due to the origin of wastewaters treated in WWTPs and the limiting environmental conditions such as temperature and nutrients. PICRUSt2 analysis inferred the total content of ARGs in the studied microbiomes and showed the highest abundance of resistance genes encoding multidrug efflux pumps, such as MexAB-OprM, AcrEF-TolC and MdtEF-TolC, followed by the modified peptidoglycan precursors, transporter genes encoding tetracycline, macrolide and phenicol resistance, and the bla operon conferring ß-lactam resistance. A number of pathogenic genera introduced by effluents, including Acinetobacter, Arcobacter, Bacteroides, Escherichia-Shigella, Klebsiella, Pseudomonas, and Salmonella, were predicted to account for the majority of efflux pump-driven multidrug resistance, while Acinetobacter, Salmonella, Bacteroides and Pseudomonas were also shown to be the predominant carriers of non-efflux ARGs conferring resistance to most of nine antibiotic classes. Taken together, we evidenced the negative impact of submarine discharges of treated effluents via alteration of physico-chemical characteristics of the water column and enrichment of bacterial community with nonindigenous taxa carrying an arsenal of ARGs, which could contribute to the further propagation of the AR in the natural environment.

Bacteria tolerant to colistin in coastal marine environment: Detection, microbiome diversity and antibiotic resistance genes' repertoire.

The global spread of mobilized colistin resistance (mcr) genes in clinical and natural environments dangerously diminishes the effectiveness of this last-resort antibiotic, becoming an urgent health threat. We used a multidisciplinary approach to detect mcr-1 gene and colistin (CL)-resistant bacteria in seawater from two Croatian public beaches. Illumina-based sequencing of metagenomic 16S rRNA was used to assess the taxonomic, functional, and antibiotic resistance genes (ARGs) profiling of the bacterial community tolerant to CL regarding different culture-based isolation methodologies. Data revealed that the choice of methodology alters the diversity and abundance of taxa accounting for the CL-resistance phenotype. The mcr-1 gene was identified by cloning and sequencing in one sample, representing the first report of mcr-1 gene in Croatia. Culturing of CL-resistant strains revealed their resistance phenotypes and concurrent production of clinically significant ß-lactamases, such as CTX-M-15, CTX-M-3 and SHV-12. We also report the first identification of blaCTX-M-15 gene in Klebsiella huaxiensis and K. michiganensis, as well as the blaTEM-1+CTX-M-3 in Serratia fonticola. ARGs profiles derived from metagenomic data and predicted by PICRUSt2, showed the highest abundance of genes encoding for multidrug efflux pumps, followed by the transporter genes accounting for the tetracycline, macrolide and phenicol resistance. Our study evidenced the multidrug resistance features of CL-tolerant bacterial communities thriving in surface beach waters. We also showed that combined application of the metagenomic approaches and culture-based techniques enabled successful detection of mcr-1 gene, which could be underreported in natural environment.

Can Local Geographically Restricted Measurements Be Used to Recover Missing Geo-Spatial Data?

The experiments conducted on the wind data provided by the European Centre for Medium-range Weather Forecasts show that 1% of the data is sufficient to reconstruct the other 99% with an average amplitude error of less than 0.5 m/s and an average angular error of less than 5 degrees. In a nutshell, our method provides an approach where a portion of the data is used as a proxy to estimate the measurements over the entire domain based only on a few measurements. In our study, we compare several machine learning techniques, namely: linear regression, K-nearest neighbours, decision trees and a neural network, and investigate the impact of sensor placement on the quality of the reconstruction. While methods provide comparable results the results show that sensor placement plays an important role. Thus, we propose that intelligent location selection for sensor placement can be done using k-means, and show that this indeed leads to increase in accuracy as compared to random sensor placement.

Self-Organizing Maps-based ocean currents forecasting system.

An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training.

Image registration and atlas-based segmentation of cardiac outflow velocity profiles.

Cardiovascular disease is the leading cause of death worldwide and for this reason computer-based diagnosis of cardiac diseases is a very important task. In this article, a method for segmentation of aortic outflow velocity profiles from cardiac Doppler ultrasound images is presented. The proposed method is based on the statistical image atlas derived from ultrasound images of healthy volunteers. The ultrasound image segmentation is done by registration of the input image to the atlas, followed by a propagation of the segmentation result from the atlas onto the input image. In the registration process, the normalized mutual information is used as an image similarity measure, while optimization is performed using a multiresolution gradient ascent method. The registration method is evaluated using an in-silico phantom, real data from 30 volunteers, and an inverse consistency test. The segmentation method is evaluated using 59 images from healthy volunteers and 89 images from patients, and using cardiac parameters extracted from the segmented image. Experimental validation is conducted using a set of healthy volunteers and patients and has shown excellent results. Cardiac parameter segmentation evaluation showed that the variability of the automated segmentation relative to the manual is comparable to the intra-observer variability. The proposed method is useful for computer aided diagnosis and extraction of cardiac parameters.

The shape of the aortic outflow velocity profile revisited: is there a relation between its asymmetry and ventricular function in coronary artery disease?

AIMS: Myocardium contracts in the beginning of ejection causing outflow acceleration, resulting in asymmetric outflow velocity profiles peaking around one-third of ejection and declining when force development declines. This article aimed to demonstrate that decreased contractility in coronary artery disease (CAD) changes outflow timing and profile symmetry. METHODS AND RESULTS: Seventy-nine patients undergoing routine full dose dobutamine stress-echo (DSE) were divided into two groups based on resting wall motion and DSE response: DSE negative (DSE(neg)) (35 of 79 patients) and positive (DSE(pos)) (44 of 79 patients) which were compared with 32 healthy volunteers. Aortic CW-Doppler traces at rest were analysed semi-automatically; time-to-peak (T(mod)), ejection-time (ET(mod)), rise-time (t(rise)), and fall-time (t(fall)) were quantified. Asymmetry (asymm) was calculated as the normalized difference of left and right half of the spectrum. Normal curves were triangular, early-peaking, whereas patients showed more rounded shapes and later peaks. T(rise) was longest in DSE(pos). T(fall) was shortest in DSE(pos), followed by controls and DSE(neg). Asymm was lowest in DSE(pos), followed by controls and DSE(neg). Abnormally symmetric profiles (asymm <0.25) were found in none of the controls, 2.9% DSE(neg), and 27.3% DSE(pos). A good correlation was found between assym and ejection fraction (EF) and T(mod)/ET(mod) and EF. Notably, an LV dynamic gradient was induced in 71.4% DSE(neg) and in 18.2% DSE(pos), associated with LV hypertrophy and supernormal (very asymmetric) traces. CONCLUSION: Decreased myocardial function results in a more symmetrical outflow, while very asymmetrical traces suggest increased contractility, potentially inducing intra-cavity gradients during DSE. Therefore, including outflow symmetry as a clinical measurement provides additional information on patients with CAD.