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Donner, E.

Publications and source records attributed to Donner, E..

2 recordsLinked to original sources

Genomic Analysis of Diverse Environmental Acinetobacter Isolates Identifies Plasmids, Antibiotic Resistance Genes, and Capsular Polysaccharides Shared with Clinical Strains

Acinetobacter baumannii, an important pathogen known for its widespread antibiotic resistance, has been the focus of extensive research within its genus, primarily involving clinical isolates. Consequently, data on environmental A. baumannii and other Acinetobacter species remain limited. Here, we utilised Illumina and Nanopore sequencing to analyse the genomes of ten Acinetobacter isolates representing six different species sourced from aquatic environments in South Australia. All ten isolates were phylogenetically distinct compared to clinical and other non-clinical Acinetobacter strains, often tens of thousands of SNPs from their nearest neighbours. Despite the genetic divergence, we identified pdif modules (sections of mobilised DNA) carrying clinically important antimicrobial resistance genes in species other than A. baumannii, including carbapenemase oxa58, tetracycline resistance gene tet(39) and macrolide resistance genes msr(E)-mph(E). All of these pdif modules were located on plasmids with high sequence homology to those circulating in globally distributed A. baumannii ST1 and ST2 clones. The environmental A. baumannii isolate characterised here (SAAb472; ST350) did not possess any native plasmids; however, it could capture two clinically important plasmids (pRAY and pACICU2) with high transfer frequencies. Furthermore, A. baumannii SAAb472 possessed virulence genes and a capsular polysaccharide type analogous to clinical strains. Our findings highlight the potential for environmental Acinetobacter species to acquire and disseminate clinically important antimicrobial resistance genes, underscoring the need for further research into the ecology and evolution of this important genus. IMPORTANCEAntimicrobial resistance (AMR) is a global threat to human, animal, and environmental health. Studying AMR in environmental bacteria is crucial to understand the emergence and dissemination of resistance genes and pathogens, and to identify potential reservoirs and transmission routes. This study provides novel insights into the genomic diversity and AMR potential of environmental Acinetobacter species. By comparing the genomes of aquatic Acinetobacter isolates with clinical and non-clinical strains, we revealed that they are highly divergent yet carry pdif modules that encode resistance to antibiotics commonly used in clinical settings. We also demonstrated that an environmental A. baumannii isolate can acquire clinically relevant plasmids and carries virulence factors similar to those of hospital-associated strains. These findings suggest that environmental Acinetobacter species may serve as reservoirs and vectors of clinically important genes. Consequently, further research is warranted to comprehensively understand the ecology and evolution of this genus.

microbiology↗

Dissociable default-mode subnetworks subserve childhood attention and cognitive flexibility: evidence from deep learning and stereotaxic electroencephalography

BackgroundCognitive flexibility encompasses the ability to efficiently shift focus and forms a critical component of goal-directed attention. The neural substrates of this process are incompletely understood in part due to difficulties in sampling the involved circuitry. MethodsStereotactic intracranial recordings that permit direct resolution of local-field potentials from otherwise inaccessible structures were employed to study moment-to-moment attentional activity in children with epilepsy during the performance of an attentional set-shifting task. A combined deep learning and model-agnostic feature explanation approach was used to analyze these data and decode attentionally-relevant neural features. Connectomic profiling of highly predictive attentional nodes was further employed to examine task-related engagement of large-scale functional networks. ResultsThrough this approach, we show that beta/gamma power within executive control, salience, and default mode networks accurately predicts single-trial attentional performance. Connectomic profiling reveals that key attentional nodes exclusively recruit dorsal default mode subsystems during attentional shifts. ConclusionsThe identification of distinct substreams within the default mode system supports a key role for this network in cognitive flexibility and attention in children. Furthermore, convergence of our results onto consistent functional networks despite significant inter-subject variability in electrode implantations supports a broader role for deep learning applied to intracranial electrodes in the study of human attention. FundingNo funds supported this specific investigation. Awards and grants supporting authors include: Canadian Institutes of Health Research (CIHR) Vanier Scholarship (NMW, HY); CIHR Frederick Banting and Charles Best Canada Graduate Scholarship Doctoral Award (SMW); CIHR Canada Graduate Scholarship Masters Award (ONA); and a CIHR project grant (GMI).

neuroscience↗