Biology subjects

Lee, R. S.

Publications and source records attributed to Lee, R. S..

4 recordsLinked to original sources

bioRxiv2018

Value representations do not explain movement selectivity in DMS-projecting dopamine neurons

Although midbrain dopamine (DA) neurons have been thought to primarily encode reward prediction error (RPE), recent studies have also found movement-related DAergic signals. For example, we recently reported that DA neurons in mice projecting to dorsomedial striatum are modulated by choices contralateral to the recording side. Here, we introduce, and ultimately reject, a candidate resolution for the puzzling RPE vs movement dichotomy, by showing how seemingly movement-related activity might be explained by an action-specific RPE. By considering both choice and RPE on a trial-by-trial basis, we find that DA signals are modulated by contralateral choice in a manner that is distinct from RPE, implying that choice encoding is better explained by movement direction. This fundamental separation between RPE and movement encoding may help shed light on the diversity of functions and dysfunctions of the DA system.

neuroscience↗

bioRxiv2018

Lineage calling can identify antibiotic resistant clones within minutes

Surveillance of drug-resistant bacteria is essential for healthcare providers to deliver effective empiric antibiotic therapy. However, traditional molecular epidemiology does not typically occur on a timescale that could impact patient treatment and outcomes. Here we present a method called genomic neighbor typing for inferring the phenotype of a bacterial sample by identifying its closest relatives in a database of genomes with metadata. We show that this technique can infer antibiotic susceptibility and resistance for both S. pneumoniae and N. gonorrhoeae. We implemented this with rapid k-mer matching, which, when used on Oxford Nanopore MinION data, can run in real time. This resulted in determination of resistance within ten minutes (sens/spec 91%/100% for S. pneumoniae and 81%/100% N. gonorrhoeae from isolates with a representative database) of sequencing starting, and for clinical metagenomic sputum samples (75%/100% for S. pneumoniae), within four hours of sample collection. This flexible approach has wide application to pathogen surveillance and may be used to greatly accelerate appropriate empirical antibiotic treatment.

bioinformatics↗

bioRxiv2018

Multiple Exposures, Reinfection, and Risk of Progression to Active Tuberculosis

A recent study reported on a tuberculosis outbreak in a largely Inuit village. Among recently infected individuals, exposure to additional active cases was associated with an increasing probability of developing active disease within a year. Using binomial risk models, we evaluated two potential mechanisms by which multiple infections during the first year following initial infection could account for increasing disease risk with increasing exposures. In the reinfection model, multiple exposures have an independent risk of becoming an infection, and infections contribute independently to active disease. In the threshold model, disease risk follows a sigmoidal function with small numbers of exposures conferring a low risk of active disease and large numbers of exposures conferring a high risk. To determine the dynamic impact of reinfection during the early phase of infection, we performed simulations from a modified Reed-Frost model of TB dynamics following spread from an initial number of cases. We parameterized this model with the maximum likelihood estimates from the reinfection and threshold models in addition to the observed distribution of exposures among recent infections. We find that both models can plausibly account for the observed increase in disease risk with increasing exposures, but the threshold model confers a better fit than a nested model without a threshold (p=0.04). Our simulations indicate that multiple exposures during this critical time period can lead to dramatic increases in outbreak size. In order to decrease TB burden in high-prevalence settings, it may be necessary to implement measures aimed at preventing repeated exposures, in addition to preventing primary infection.

epidemiology↗

bioRxiv2018

The changing landscape of VREfm in Victoria, Australia: a state-wide genomic snapshot

Vancomycin-resistant Enterococcus faecium (VREfm) represent a major source of nosocomial infection worldwide. In Australia, the vanB genotype is dominant; however there has been a recent increase in the predominantly plasmid-encoded vanA genotype, prompting investigation into the genomic epidemiology of VREfm in this context.\n\nMaterials and MethodsA cross-sectional study of VREfm in Victoria, Australia (Nov.10th - Dec.9th, 2015). A total of 321 VREfm isolates (from 286 patients) were collected and whole-genome sequenced with Illumina NextSeq. Single nucleotide polymorphisms (SNPs) were used to assess relatedness. Multi-locus sequence types (STs), and genes associated with resistance and virulence were identified. The vanA-harbouring plasmid from an isolate from each ST was assembled using long-read data.\n\nResultsvanA-VREfm comprised 17.8% of isolates. ST203, ST80 and a pstS(-) clade, ST1421, predominated (30.5%, 30.5% and 37.2% of vanA-VREfm, respectively). Most vanB-VREfm were ST796 (77.7%). vanA-VREfm isolates were closely-related within hospitals vs. between them (core SNPs 10 [interquartile range 1-357] vs. 356 [179-416] respectively), suggesting discrete introductions of vanA-VREfm, with subsequent intra-hospital transmission. In contrast, vanB-VREfm had similar core SNP distributions within vs. between hospitals, due to widespread dissemination of ST796. Overall, vanA-harbouring plasmids differed across STs, and with exception of ST78 and ST796, Tn1546 transposons also varied.\n\nConclusionsvanA-VREfm in Victoria is associated with multiple STs, and is not solely mediated by a single shared plasmid/Tn1546 transposon; clonal transmission appears to play an important role, predominantly within, rather than between, hospitals. In contrast, vanB-VREfm appears to be well-established and widespread across Victorian healthcare institutions.

genomics↗