Biology subjects

Lewandowski, K.

Publications and source records attributed to Lewandowski, K..

3 recordsLinked to original sources

bioRxiv2018

Assessment of Metagenomic MinION and Illumina sequencing as an approach for the recovery of whole genome sequences of chikungunya and dengue viruses directly from clinical samples.

The recent global emergence and re-emergence of arboviruses has caused significant human disease. Common vectors, symptoms and geographical distribution make differential diagnosis both important and challenging. We performed metagenomic sequencing using both the Illumina MiSeq and the portable Oxford Nanopore MinION to study the feasibility of whole genome sequencing from clinical samples containing chikungunya or dengue virus, two of the most important arboviruses. Direct metagenomic sequencing of nucleic acid extracts from serum and plasma without viral enrichment allowed for virus and coinfection identification, subtype determination and in the majority of cases elucidated complete or near-complete genomes adequate for phylogenetic analysis. This work demonstrates that metagenomic whole genome sequencing is feasible for over 90% and 80% of chikungunya and dengue virus PCR-positive patient samples respectively. It confirms the feasibility of field metagenomic sequencing for these and likely other RNA viruses, highlighting the applicability of this approach to front-line public health.

microbiology↗

bioRxiv2018

Detection of viral pathogens with multiplex Nanopore MinION sequencing: be careful with cross-talk

Metagenomic sequencing with the Oxford Nanopore MinION sequencer offers potential for point-of-care testing of infectious diseases in clinical settings. To improve cost-effectiveness, multiplexing of several, barcoded samples upon a single flow cell will be required during sequencing. We generated a unique sequencing dataset to assess the extent and source of cross barcode contamination caused by multiplex MinION sequencing. Sequencing libraries for three different viruses, including influenza A, dengue and chikungunya, were prepared separately and sequenced on individual flow cells. We also pooled the respective libraries and performed multiplex sequencing. We identified 0.056% of total reads in the multiplex sequencing data that were assigned to incorrect barcodes. Chimeric reads were the predominant source of this error. Our findings highlight the need for careful filtering of multiplex sequencing data before downstream analysis, and the trade-off between sensitivity and specificity that applies to the barcode demultiplexing methods.

bioinformatics↗

bioRxiv2018

Individual Variation in Brain Network Topology and Social Cognitive Ability

BackgroundSocial cognitive ability is a significant determinant of functional outcome and deficits in social cognition are a disabling symptom of psychotic disorders. The neurobiological underpinnings of social cognition are not well understood, hampering our ability to ameliorate these deficits.\n\nObjectiveUsing resting-state fMRI (functional magnetic resonance imaging) and a trans-diagnostic, data-driven analytic strategy, we sought to identify the brain network basis of emotional intelligence, a key domain of social cognition.\n\nMethodsStudy participants included 60 participants with a diagnosis of schizophrenia or schizoaffective disorder and 46 healthy comparison participants. All participants underwent a resting-state fMRI scan. Emotional Intelligence was measured using the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). A connectome-wide analysis of brain connectivity examined how each individual brain voxels connectivity correlated with emotional intelligence using multivariate distance matrix regression (MDMR).\n\nResultsWe identified a region in the left superior parietal lobule (SPL) where individual network topology predicted emotional intelligence. Specifically, the association of this region with the Default Mode Network predicted higher emotional intelligence and association with the Dorsal Attention Network predicted lower emotional intelligence. This correlation was observed in both schizophrenia and healthy comparison participants.\n\nConclusionPrevious studies have demonstrated individual variance in brain network topology but the cognitive or behavioral relevance of these differences was undetermined. We observe that the left SPL, a region of high individual variance at the cytoarchitectonic level, also demonstrates individual variance in its association with large scale brain networks and that network topology predicts emotional intelligence.

neuroscience↗