16 research outputs found
Reliable and accurate diagnostics from highly multiplexed sequencing assays
Scalable, inexpensive, and secure testing for SARS-CoV-2 infection is crucial for control of the novel coronavirus pandemic. Recently developed highly multiplexed sequencing assays (HMSAs) that rely on high-throughput sequencing can, in principle, meet these demands, and present promising alternatives to currently used RT-qPCR-based tests. However, reliable analysis, interpretation, and clinical use of HMSAs requires overcoming several computational, statistical and engineering challenges. Using recently acquired experimental data, we present and validate a computational workflow based on kallisto and bustools, that utilizes robust statistical methods and fast, memory efficient algorithms, to quickly, accurately and reliably process high-throughput sequencing data. We show that our workflow is effective at processing data from all recently proposed SARS-CoV-2 sequencing based diagnostic tests, and is generally applicable to any diagnostic HMSA
Reliable and accurate diagnostics from highly multiplexed sequencing assays
Scalable, inexpensive, and secure testing for SARS-CoV-2 infection is crucial for control of the novel coronavirus pandemic. Recently developed highly multiplexed sequencing assays (HMSAs) that rely on high-throughput sequencing can, in principle, meet these demands, and present promising alternatives to currently used RT-qPCR-based tests. However, reliable analysis, interpretation, and clinical use of HMSAs requires overcoming several computational, statistical and engineering challenges. Using recently acquired experimental data, we present and validate a computational workflow based on kallisto and bustools, that utilizes robust statistical methods and fast, memory efficient algorithms, to quickly, accurately and reliably process high-throughput sequencing data. We show that our workflow is effective at processing data from all recently proposed SARS-CoV-2 sequencing based diagnostic tests, and is generally applicable to any diagnostic HMSA
Comparative genomics profiling of clinical isolates of Aeromonas salmonicida using DNA microarrays
BACKGROUND: Aeromonas salmonicida has been isolated from numerous fish species and shows wide variation in virulence and pathogenicity. As part of a larger research program to identify virulence genes and candidates for vaccine development, a DNA microarray was constructed using a subset of 2024 genes from the draft genome sequence of A. salmonicida subsp. salmonicida strain A449. The microarray included genes encoding known virulence-associated factors in A. salmonicida and homologs of virulence genes of other pathogens. We used microarray-based comparative genomic hybridizations (M-CGH) to compare selected A. salmonicida sub-species and other Aeromonas species from different hosts and geographic locations. RESULTS: Results showed variable carriage of virulence-associated genes and generally increased variation in gene content across sub-species and species boundaries. The greatest variation was observed among genes associated with plasmids and transposons. There was little correlation between geographic region and degree of variation for all isolates tested. CONCLUSION: We have used the M-CGH technique to identify subsets of conserved genes from amongst this set of A. salmonicida virulence genes for further investigation as potential vaccine candidates. Unlike other bacterial characterization methods that use a small number of gene or DNA-based functions, M-CGH examines thousands of genes and/or whole genomes and thus is a more comprehensive analytical tool for veterinary or even human health research
Complexity of Transcriptomic Data Analysis and Implications for Biological Discovery
Over the past decade, the advancement of ‘omics’ technologies has ushered in a new era for the life sciences. Given the high-throughput nature of omics technologies, this era is characterized by unique computational challenges pertaining to data size and dimensionality, and technical and biological noise. Concurrently, it offers opportunities, as global, untargeted, and parallel measurement of large amounts of information often captures unexpected insights.
This thesis describes challenges inherent to the omics era of life sciences, particularly highlighting the increasing importance of merging expertise in biology and computer science. It describes the development of multiple software tools designed to address several of these challenges, which were immediately adopted and widely implemented in transcriptomics and proteomics research. Additionally, it contains three chapters focused on unraveling previously unquantifiable information, including the interpretation of sequencing data from organisms with low-quality reference genome assemblies and workflows for identifying novel viruses using single-cell RNA sequencing data already massively generated in research, healthcare, and agriculture.</p
Single cell RNA sequencing paradigm after chronic loss of inhibition in a pre-motor avian circuit
Mastering essential motor skills is crucial for an animal's survival and reproduction, enabling it to endure diverse perturbations throughout its lifespan, such as trauma, disease, and aging. What mechanisms orchestrate brain circuit reorganization and recovery to maintain stability of behavioral output during the continued presence of a disturbance? In this study, we investigate the consequences at the behavioral, neuronal, and transcriptome level of chronically perturbing a complex behavior over time. Our electrophysiology recordings suggest a relationship between offline activity dynamics and circuit restoration for behavior. Furthermore, single-cell RNA sequencing reveals cellular mechanisms underlying behavioral recovery suggesting a role for synaptic plasticity in this restoration process mediated by microglia and MHC class I. Our findings offer compelling evidence that the adult brain has the ability to surmount prolonged circuit perturbations through the utilization of offline activity and repair mediated by microglia.
This dataset contains the single-cell RNA sequencing files in two control and two experimental animals ( after chronic muting of interneurons) in the avian pre-motor circuit. This is the first dataset of its kind where a behavioral manipulation leading to drastic changes is compared against a control in the zebra finch HVC.
Please contact us with any questions, comments or concerns: [email protected] , [email protected], [email protected], [email protected] to lack of space the missing file for SE7425 SA112356 S1 L003 R1 001 can be found with our other dataset with DOI: https://doi.org/10.22002/3ta8v-gj982 . 
Behavioral and neuronal changes after chronic loss of inhibition in a pre-motor avian circuit
Mastering essential motor skills is crucial for an animal's survival and reproduction, enabling it to endure diverse perturbations throughout its lifespan, such as trauma, disease, and aging. What mechanisms orchestrate brain circuit reorganization and recovery to maintain stability of behavioral output during the continued presence of a disturbance? In this study, we investigate the consequences at the behavioral, neuronal, and transcriptome level of chronically perturbing a complex behavior over time. Our electrophysiology recordings suggest a relationship between offline activity dynamics and circuit restoration for behavior. Furthermore, single-cell RNA sequencing reveals cellular mechanisms underlying behavioral recovery suggesting a role for synaptic plasticity in this restoration process mediated by microglia and MHC class I. Our findings offer compelling evidence that the adult brain has the ability to surmount prolonged circuit perturbations through the utilization of offline activity and repair mediated by microglia.
This dataset contains the last file belongs to the first control animal (starting with SE_) from one animal left over from the single-cell RNA sequencing files uploaded with DOI: 10.22002/ednra-nn006.
The following dataset that contains .wav files pertain to the songs the animals produced after either control or interneuron muting virus injection into the pre-motor nucleus of adult male zebra finches. This is the first chronic manipulation of the interneuron population in this pre -motor circuit, which surprisingly is a large-scale perturbation the system can overcome within 60-90 days after loss of precise execution of behavior for about 40-80 days.
The last dataset that contains .mat files pertains to the electrophysiology, sounds and head-movement data collected during chronic electrophysiology recordings either in control or interneuron muted animals. This is the first dataset of this type to be recorded.
Please contact us with any questions, comments or concerns: [email protected] , [email protected], [email protected], [email protected] .mat files that start with B138 are of a chronically implanted animal's sound, head-movement and electrophysiology data with muting of interneurons in HVC. The .mat files with ID PK31 are of a control animal with a similar implant.
The .zip file contains sound recordings for animals that we performed acute head fixed electrophysiology. IDs of animals label folders in which you find .wav files that were curated at different times during the perturbation. V654, V652 are control animals with normal song, while V664,V668,V670,V671 animals injected with interneuron muting virus recorded for electrophysiology at 3-6 days post injection; V647,V648 are animals injected with interneuron muting virus recorded at 20 days post injection and at 70 days post injection ( when their song recovered) for electrophysiology. 
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Fast and accurate diagnostics from highly multiplexed sequencing assays
Scalable, inexpensive, accurate, and secure testing for SARS-CoV-2 infection is crucial for control of the novel coronavirus pandemic. Recently developed highly multiplexed sequencing assays that rely on high-throughput sequencing (HMSAs) can, in principle, meet these demands, and present promising alternatives to currently used RT-qPCR-based tests. However, the analysis and interpretation of HMSAs requires overcoming several computational and statistical challenges. Using recently acquired experimental data, we present and validate an accurate and fast computational testing workflow based on kallisto and bustools, that utilize robust statistical methods and fast, memory efficient algorithms for processing high-throughput sequencing data. We show that our workflow is effective at processing data from all recently proposed SARS-CoV-2 sequencing based diagnostic tests, and is generally applicable to any diagnostic HMSAs
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Selective Serotonin Reuptake Inhibitors within Cells: Temporal Resolution in Cytoplasm, Endoplasmic Reticulum, and Membrane.
Selective serotonin reuptake inhibitors (SSRIs) are the most prescribed treatment for individuals experiencing major depressive disorder. The therapeutic mechanisms that take place before, during, or after SSRIs bind the serotonin transporter (SERT) are poorly understood, partially because no studies exist on the cellular and subcellular pharmacokinetic properties of SSRIs in living cells. We studied escitalopram and fluoxetine using new intensity-based, drug-sensing fluorescent reporters targeted to the plasma membrane, cytoplasm, or endoplasmic reticulum (ER) of cultured neurons and mammalian cell lines. We also used chemical detection of drug within cells and phospholipid membranes. The drugs attain equilibrium in neuronal cytoplasm and ER at approximately the same concentration as the externally applied solution, with time constants of a few s (escitalopram) or 200-300 s (fluoxetine). Simultaneously, the drugs accumulate within lipid membranes by ≥18-fold (escitalopram) or 180-fold (fluoxetine), and possibly by much larger factors. Both drugs leave cytoplasm, lumen, and membranes just as quickly during washout. We synthesized membrane-impermeant quaternary amine derivatives of the two SSRIs. The quaternary derivatives are substantially excluded from membrane, cytoplasm, and ER for >2.4 h. They inhibit SERT transport-associated currents sixfold or 11-fold less potently than the SSRIs (escitalopram or fluoxetine derivative, respectively), providing useful probes for distinguishing compartmentalized SSRI effects. Although our measurements are orders of magnitude faster than the therapeutic lag of SSRIs, these data suggest that SSRI-SERT interactions within organelles or membranes may play roles during either the therapeutic effects or the antidepressant discontinuation syndrome.SIGNIFICANCE STATEMENT Selective serotonin reuptake inhibitors stabilize mood in several disorders. In general, these drugs bind to SERT, which clears serotonin from CNS and peripheral tissues. SERT ligands are effective and relatively safe; primary care practitioners often prescribe them. However, they have several side effects and require 2-6 weeks of continuous administration until they act effectively. How they work remains perplexing, contrasting with earlier assumptions that the therapeutic mechanism involves SERT inhibition followed by increased extracellular serotonin levels. This study establishes that two SERT ligands, fluoxetine and escitalopram, enter neurons within minutes, while simultaneously accumulating in many membranes. Such knowledge will motivate future research, hopefully revealing where and how SERT ligands engage their therapeutic target(s)
Comparative genomics profiling of clinical isolates of using DNA microarrays-4
<p><b>Copyright information:</b></p><p>Taken from "Comparative genomics profiling of clinical isolates of using DNA microarrays"</p><p>BMC Genomics 2006;7():43-43.</p><p>Published online 7 Mar 2006</p><p>PMCID:PMC1434746.</p><p>Copyright © 2006 Nash et al; licensee BioMed Central Ltd.</p>n size. The amplicons were "binned" in 50 bp increments (to 1900 bp) then in 200 bp increments (from 2000 to 3000 bp). There were only 4 amplicons of size over 3000 bp