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Baker, D.

Publications and source records attributed to Baker, D..

9 recordsLinked to original sources

Noninvasive Vagus Nerve Stimulation Alters Neural Response and Physiological Autonomic Tone to Noxious Thermal Challenge

The mechanisms by which noninvasive vagal nerve stimulation (nVNS) affect central and peripheral neural circuits that subserve pain and autonomic physiology are not clear, and thus remain an area of intense investigation. Effects of nVNS vs sham stimulation on subject responses to five noxious thermal stimuli (applied to left lower extremity), were measured in 30 healthy subjects (n=15 sham and n=15 nVNS), with fMRI and physiological galvanic skin response (GSR). With repeated noxious thermal stimuli a group x time analysis showed a significantly (p < .001) decreased response with nVNS in bilateral primary and secondary somatosensory cortices (SI and SII), left dorsoposterior insular cortex, bilateral paracentral lobule, bilateral medial dorsal thalamus, right anterior cingulate cortex, and right orbitofrontal cortex. A group x time x GSR analysis showed a significantly decreased response in nVNS group (p < .0005) in bilaterally in SI, lower and mid medullary brainstem, and inferior occipital cortex. Finally, nVNS treatment showed decreased activity in pronociceptive brainstem nuclei (e.g. the reticular nucleus and rostral ventromedial medulla) and key autonomic integration nuclei (e.g. the rostroventrolateral medulla, nucleus ambiguous, and dorsal motor nucleus of the vagus nerve). In aggregate, noninvasive vagal nerve stimulation reduced the physiological response to noxious thermal stimuli and impacted neural circuits important for pain processing and autonomic output.

neuroscience

Internal noise in contrast discrimination propagates forwards from early visual cortex

Human contrast discrimination performance is limited by transduction nonlinearities and variability of the neural representation (noise). Whereas the nonlinearities have been well-characterised, there is less agreement about the specifics of internal noise. Psychophysical models assume that it impacts late in sensory processing, whereas neuroimaging and intracranial electrophysiology studies suggest that the noise is much earlier. We investigated whether perceptually-relevant internal noise arises in early visual areas or later decision making areas. We recorded EEG and MEG during a two-interval-forced-choice contrast discrimination task and used multivariate pattern analysis to decode target/non-target and selected/non-selected intervals from evoked responses. We found that perceptual decisions could be decoded from both EEG and MEG signals, even when the stimuli in both intervals were physically identical. Above-chance decision classification started <100ms after stimulus onset, suggesting that neural noise affects sensory signals early in the visual pathway. Classification accuracy increased over time, peaking at >500ms. Applying multivariate analysis to separate anatomically-defined brain regions in MEG source space, we found that occipital regions were informative early on but then information spreads forwards across parietal and frontal regions. This is consistent with neural noise affecting sensory processing at multiple stages of perceptual decision making. We suggest how early sensory noise might be resolved with Birdsalls linearisation, in which a dominant noise source obscures subsequent nonlinearities, to allow the visual system to preserve the wide dynamic range of early areas whilst still benefitting from contrast-invariance at later stages. A preprint of this work is available at: http://dx.doi.org/10.1101/364612

neuroscience

Antibody responses to the Zika virus polyprotein in pregnant and non-pregnant macaques

The specificity of the antibody response against Zika virus (ZIKV) is not well-characterized. This is due, in part, to the antigenic similarity between ZIKV and closely related dengue virus (DENV) serotypes. Since these and other similar viruses co-circulate, are spread by the same mosquito species, and can cause similar acute clinical syndromes, it is difficult to disentangle ZIKV-specific antibody responses from responses to closely-related arboviruses in humans. Here we use high-density peptide microarrays to profile anti-ZIKV antibody reactivity in pregnant and non-pregnant macaque monkeys with known exposure histories and compare these results to reactivity following DENV infection. We also compare cross-reactive binding of ZIKV-immune sera to the full proteomes of 28 arboviruses. We independently confirm a purported ZIKV-specific IgG antibody response targeting ZIKV nonstructural protein 2B (NS2B) that was recently reported in ZIKV-infected people and we show that antibody reactivity in pregnant animals can be detected as late as 127 days post-infection (dpi). However, we also show that these responses wane over time, sometimes rapidly, and in one case the response was elicited following DENV infection in a previously ZIKV-exposed animal. These results suggest epidemiologic studies assessing seroprevalence of ZIKV immunity using linear epitope-based strategies will remain challenging to interpret due to susceptibility to false positive results. However, the method used here demonstrates the potential for rapid profiling of proteome-wide antibody responses to a myriad of neglected diseases simultaneously and may be especially useful for distinguishing antibody reactivity among closely related pathogens.\n\nAuthor summaryZIKV has emerged as a vector-borne pathogen capable of causing serious illness in infected adults and congenital birth defects. The vulnerability of communities to future ZIKV outbreaks will depend, in part, on the prevalence and longevity of protective immunity, thought to be mediated principally by antibodies. We currently lack diagnostic assays able to differentiate ZIKV-specific antibodies from antibodies produced following infection with closely related DENV, and we do not know how long anti-ZIKV responses are detectable. Here we profile antibodies recognizing linear epitopes throughout the entire ZIKV polyprotein, and we profile cross-reactivity with the proteomes of other co-endemic arboviruses. We show that while ZIKV-specific antibody binding can be detected, these responses are generally weak and ephemeral, and false positives may arise through DENV infection. This may complicate efforts to discern ZIKV infection and to determine ZIKV seroprevalence using linear epitope-based assays. The method used in this study, however, has promise as a tool for profiling antibody responses for a broad array of neglected tropical diseases and other pathogens and in distinguishing serology of closely-related viruses.

microbiology

Binaural fusion involves weak interaural suppression

The brain combines sounds from the two ears, but what is the algorithm used to achieve this summation of signals? Here we combine psychophysical amplitude modulation discrimination and steady-state electroencephalography (EEG) data to investigate the architecture of binaural combination for amplitude-modulated tones. Discrimination thresholds followed a dipper shaped function of pedestal modulation depth, and were consistently lower for binaural than monaural presentation of modulated tones. The EEG responses were greater for binaural than monaural presentation of modulated tones, and when a masker was presented to one ear, it produced only weak suppression of the response to a signal presented to the other ear. Both data sets were well-fit by a computational model originally derived for visual signal combination, but with suppression between the two channels (ears) being much weaker than in binocular vision. We suggest that the distinct ecological constraints on vision and hearing can explain this difference, if it is assumed that the brain avoids over-representing sensory signals originating from a single object. These findings position our understanding of binaural summation in a broader context of work on sensory signal combination in the brain, and delineate the similarities and differences between vision and hearing.

neuroscience

Community-driven data analysis training for biology

The primary problem with the explosion of biomedical datasets is not the data itself, not computational resources, and not the required storage space, but the general lack of trained and skilled researchers to manipulate and analyze these data. Eliminating this problem requires development of comprehensive educational resources. Here we present a community-driven framework that enables modern, interactive teaching of data analytics in life sciences and facilitates the development of training materials. The key feature of our system is that it is not a static but a continuously improved collection of tutorials. By coupling tutorials with a web-based analysis framework, biomedical researchers can learn by performing computation themselves through a web-browser without the need to install software or search for example datasets. Our ultimate goal is to expand the breadth of training materials to include fundamental statistical and data science topics and to precipitate a complete re-engineering of undergraduate and graduate curricula in life sciences.

bioinformatics

A critical comparison of technologies for a plant genome sequencing project

A high quality genome sequence of your model organism is an essential starting point for many studies. Old clone based methods are slow and expensive, whereas faster, cheaper short read only assemblies can be incomplete and highly fragmented, which minimises their usefulness. The last few years have seen the introduction of many new technologies for genome assembly. These new technologies and new algorithms are typically benchmarked on microbial genomes or, if they scale appropriately, human. However, plant genomes can be much more repetitive and larger than human, and plant biology makes obtaining high quality DNA free from contaminants difficult. Reflecting their challenging nature we observe that plant genome assembly statistics are typically poorer than for vertebrates. Here we compare Illumina short read, PacBio long read, 10x Genomics linked reads, Dovetail Hi-C and BioNano Genomics optical maps, singly and combined, in producing high quality long range genome assemblies of the potato species S. verrucosum. We benchmark the assemblies for completeness and accuracy, as well as DNA, compute requirements and sequencing costs. We expect our results will be helpful to other genome projects, and that these datasets will be used in benchmarking by assembly algorithm developers.

genomics

Epigenetic resetting of human pluripotency

Much attention has focussed on conversion of human pluripotent stem cells (PSC) to a more naive developmental status. Here we provide a method for resetting via transient histone deacetylase inhibition. The protocol is effective across multiple PSC lines and can proceed without karyotype change. Reset cells can be expanded without feeders with a doubling time of around 24 hours. WNT inhibition stabilises the resetting process. The transcriptome of reset cells diverges markedly from primed PSC and shares features with human inner cell mass (ICM). Reset cells activate expression of primate-specific transposable elements. DNA methylation is globally reduced to the level in the ICM but is non-random, with gain of methylation at specific loci. Methylation imprints are mostly lost, however. Reset cells can be re-primed to undergo tri-lineage differentiation and germline specification. In female reset cells, appearance of bi-allelic X-linked gene transcription indicates re-activation of the silenced X chromosome. On re-conversion to primed status, XIST-induced silencing restores monoallelic gene expression. The facile and robust conversion routine with accompanying data resources will enable widespread utilisation, interrogation, and refinement of candidate naive cells.

developmental biology

High-Throughput Characterization of Protein-Protein Interactions by Reprogramming Yeast Mating

High-throughput methods for screening protein-protein interactions (PPIs) enable the rapid characterization of engineered binding proteins and interaction networks. While existing methods are powerful, none allow quantitative library-on-library characterization of PPIs in a modifiable extracellular environment. Here, we show that sexual agglutination of S. cerevisiae can be reprogrammed to link PPI strength with mating efficiency using yeast synthetic agglutination (YSA). Validation of YSA with 96 previously characterized interactions shows a strong log-linear relationship between mating efficiency and PPI strength for interactions with KDs ranging from 500 pM to 25 M. Using induced chromosomal translocation to pair barcodes representing interacting proteins, thousands of distinct interactions can be screened in a single pot. YSA binding interactions occur in a controllable extracellular environment, and thus studying the effects of environmental factors on PPI networks is possible. YSA enables the high-throughput, quantitative characterization of PPI networks in a fully defined extracellular environment at a library-on-library scale.

synthetic biology

The Rosetta all-atom energy function for macromolecular modeling and design

Over the past decade, the Rosetta biomolecular modeling suite has informed diverse biological questions and engineering challenges ranging from interpretation of low-resolution structural data to design of nanomaterials, protein therapeutics, and vaccines. Central to Rosettas success is the energy function: amodel parameterized from small molecule and X-ray crystal structure data used to approximate the energy associated with each biomolecule conformation. This paper describes the mathematical models and physical concepts that underlie the latest Rosetta energy function, beta_nov15. Applying these concepts,we explain how to use Rosetta energies to identify and analyze the features of biomolecular models.Finally, we discuss the latest advances in the energy function that extend capabilities from soluble proteins to also include membrane proteins, peptides containing non-canonical amino acids, carbohydrates, nucleic acids, and other macromolecules.

biophysics