Biology subjects

Baker, B.

Publications and source records attributed to Baker, B..

36 records · Page 2Linked to original sources

bioRxiv2025

Perivascular matrix densification dysregulates angiogenesis and activates pro-inflammatory endothelial cells

Fibrosis is central to numerous fatal conditions including solid cancers, pulmonary fibrosis, cirrhosis and post-infarct cardiac fibrosis amongst many others, thereby collectively contributing to 45% of all deaths in developed nations. The potential for fibrosis across most organ systems may stem from its connections to wound healing and the ubiquitous presence of vascular endothelium. Endothelial cells (ECs) and angiogenesis, cells and associated biological program central to wound healing, have been heavily implicated in many organ-specific fibroses, but the relationship between angiogenesis and fibrogenesis remains debated and little has been established in terms of how the EC phenotype governs tissue healing vs. fibrosis. Here, we examine a murine lung injury model enabling EC lineage tracing and observe the invasion of aberrant ECs from the bronchial microvasculature following lung injury along with concurrent densification of matrix fibers surrounding these vessels. To investigate the underlying mechanisms governing their appearance, we established a microphysiological system (MPS) of arteriole/venule-scale microvessels embedded within a tunable stromal mimetic matrix and find that heightened extracellular matrix fiber density activates ECs, drives endothelial to mesenchymal transition, and promotes aberrant tip EC (ATEC) invasion into the matrix. ATECs remain adherent to fibrotic matrix and possess a pro-inflammatory phenotype that secretes TGF-{beta}2. Notably, our studies establish that the formation of ATECs is gated by destabilization of endothelial adherens junction upon EC adhesion to fibrous matrix, and associated regulation of TGF-{beta} signaling that is mediated by a novel VE-cadherin - TGF-{beta}R2 axis. The current lack of effective anti-fibrotic therapies suggests potential critical involvement of other cell types such as ECs, and our findings suggest new contributions of ECs to fibrotic progression that may better inform future targets for novel anti-fibrotic therapeutics.

bioengineering↗

bioRxiv2024

Long-read sequencing of hundreds of diverse brains provides insight into the impact of structural variation on gene expression and DNA methylation

Structural variants (SVs) drive gene expression in the human brain and are causative of many neurological conditions. However, most existing genetic studies have been based on short-read sequencing methods, which capture fewer than half of the SVs present in any one individual. Long-read sequencing (LRS) enhances our ability to detect disease-associated and functionally relevant structural variants; however, its application in large-scale genomic studies has been limited by challenges in sample preparation and high costs. Here, we leverage a new scalable wet-lab protocol and computational pipeline for whole-genome Oxford Nanopore Technologies sequencing and apply it to neurologically normal control samples from the North American Brain Expression Consortium (NABEC) (European ancestry) and Human Brain Collection Core (HBCC) (African or African admixed ancestry) cohorts. Through this work, we present a publicly available long-read resource from 351 human brain samples (median N50: 27 Kbp and at an average depth of ~40x genome coverage). We discover approximately 234,905 SVs and produce locally phased assemblies that cover 95% of all protein-coding genes in GRCh38. To resolve cis-regulatory effects, we develop ASM-LR, a method for allele-specific methylation analysis from long-read data, revealing both strong and subtle regulatory effects, including numerous novel methylation QTLs masked in unphased models. Our results highlight the power of haplotype-resolved methylation to uncover regulatory mechanisms and establish a foundational resource for exploring how genetic variation shapes gene expression and epigenetic architecture across diverse ancestries.

genomics↗

bioRxiv2024

CNV-Finder: Streamlining Copy Number Variation Discovery

Copy Number Variations (CNVs) play pivotal roles in the etiology of complex diseases and are variable across diverse populations. Understanding the association between CNVs and disease susceptibility is significant in disease genetics research and often requires analysis of large sample sizes. One of the most cost-effective and scalable methods for detecting CNVs is based on normalized signal intensity values, such as Log R Ratio (LRR) and B Allele Frequency (BAF), from Illumina genotyping arrays. In this study, we present CNV-Finder, a novel pipeline integrating deep learning techniques on array data, specifically a Long Short-Term Memory (LSTM) network, to expedite the large-scale identification of CNVs within predefined genomic regions. This facilitates efficient prioritization of samples for time-consuming or costly subsequent analyses such as Multiplex Ligation-dependent Probe Amplification (MLPA), short-read, and long-read whole genome sequencing. We incorporate four genes to establish our methods--Parkin (PRKN), Leucine Rich Repeat And Ig Domain Containing 2 (LINGO2), Microtubule Associated Protein Tau (MAPT), and alpha-Synuclein (SNCA)--which may be relevant to neurological diseases such as Alzheimers disease (AD), Parkinsons disease (PD), Progressive Supranuclear Palsy (PSP), or related disorders such as essential tremor (ET). By training our models on expert-annotated samples and validating them across diverse cohorts, including those from the Global Parkinsons Genetics Program (GP2) and additional dementia-specific databases, we demonstrate the efficacy of CNV-Finder in accurately detecting deletions and duplications. Our pipeline outputs app-compatible files for visualization within CNV-Finders interactive web application. This interface enables researchers to review predictions and filter displayed samples by model prediction values, LRR range, and variant count in order to explore or confirm results. Our pipeline integrates this human feedback to enhance model performance and reduce false positive rates. Through a series of comprehensive analyses and validations using visual inspection, MLPA, short-read, and long-read sequencing data, we demonstrate the robustness and adaptability of CNV-Finder in identifying CNVs with regions of varied size, probe density, and noise. Our findings highlight the significance of contextual understanding and human expertise in enhancing the precision of CNV identification, particularly in complex genomic regions like 17q21.31. The CNV-Finder pipeline is a scalable, publicly available resource for the scientific community, available on GitHub (https://github.com/GP2code/CNV-Finder; DOI 10.5281/zenodo.14182563). CNV-Finder not only expedites accurate candidate identification but also significantly reduces the manual workload for researchers, enabling future targeted validation and downstream analyses in regions or phenotypes of interest.

bioinformatics↗

bioRxiv2024

Template-driven dynamic functional network connectivity predicts medication response for major depression and bipolar disorders

The process of finding reliable treatment for major depression and bipolar disorder can be arduous. The myriad behavioral symptoms presented by patients and resistance to treatment from particular medication classes complicate standard diagnostic and prescription methodologies, often requiring multiple attempted treatments during which symptoms may still be present. Physiological information such as neuroimaging scans may help to alleviate some of the uncertainty surrounding diagnosis and treatment when incorporated into a clinical setting. Changes in functional magnetic resonance imaging show particular promise, as the incorporation of dynamical information may provide insights into physiological changes prior to static, structural changes. In this work, we present a novel method for generating robust and replicable dynamic functional network connectivity (dFNC) features from neuroimaging data using a template of dynamic states derived from a large, non-affected data set. We demonstrate that this template-driven dFNC approach expands on standard dFNC approaches by allowing for the derivation of a continuous state-contribution time series. We demonstrate that the derived biomarkers can support high predictive performance for the identification of medication class and non-responders while also expanding the set of biomarkers available for studying differences in mood disorder medication response.

neuroscience↗

bioRxiv2024

Local photo-crosslinking of native tissue matrix regulates cell function

Within most tissues, the extracellular microenvironment provides mechanical cues that guide cell fate and function. Changes in the extracellular matrix such as aberrant deposition, densification and increased crosslinking are hallmarks of late-stage fibrotic diseases that often lead to organ dysfunction. Biomaterials have been widely used to mimic the mechanical properties of the fibrotic matrix and study cell function. However, the initiation of fibrosis has largely been overlooked, due to the challenges in recapitulating early fibrotic lesions within the native extracellular microenvironment. Using visible light mediated photochemistry, we induced local crosslinking and stiffening of extracellular matrix proteins within ex vivo murine and human tissue. In ex vivo lung tissue of epithelial cell lineage-traced mice, local matrix crosslinking mimicked early fibrotic lesions that increased alveolar epithelial cell spreading, differentiation and extracellular matrix remodeling. However, inhibition of cytoskeletal tension or integrin engagement reduced epithelial cell spreading and differentiation, resulting in alveolar epithelial cell dedifferentiation and reduced extracellular matrix deposition. Our findings emphasize the role of local extracellular matrix crosslinking and remodeling in early-stage tissue fibrosis and have implications for ex vivo disease modeling and applications to other tissues.

bioengineering↗

bioRxiv2024

Extremely acidic proteomes and metabolic flexibility in bacteria and highly diversified archaea thriving in geothermal chaotropic brines

Few described archaeal, and fewer bacterial, lineages thrive at salt-saturating conditions, such as solar saltern crystallizers (salinity above 30%-w/v). They accumulate molar K+ cytoplasmic concentrations to maintain osmotic balance ( salt-in strategy), and have proteins adaptively enriched in negatively charged, acidic amino acids. Here, we analyzed metagenomes and metagenome-assembled genomes (MAGs) from geothermally influenced hypersaline ecosystems with increasing chaotropicity in the Danakil Depression. Normalized abundances of universal single-copy genes confirmed that haloarchaea and Nanohaloarchaeota encompass 99% of microbial communities in the near life-limiting conditions of the Western-Canyon Lakes (WCLs). Danakil metagenome- and MAG-inferred proteomes, compared to those of freshwater, seawater and solar saltern ponds up to saturation (6-14-32% salinity), showed that WCL archaea encode the most acidic proteomes ever observed (median protein isoelectric points [≤]4.4). We identified previously undescribed Halobacteria families as well as an Aenigmatarchaeota family and a bacterial phylum independently adapted to extreme halophily. Despite phylum-level diversity decreasing with increasing salinity-chaotropicity, and unlike in solar salterns, adapted archaea exceedingly diversified in Danakil ecosystems, challenging the notion of decreasing diversity under extreme conditions. Metabolic flexibility to utilize multiple energy and carbon resources generated by local hydrothermalism along feast-and-famine strategies seemingly shape microbial diversity in these ecosystems near life limits.

microbiology↗

bioRxiv2024

Assessing methylation detection for primary human tissue using Nanopore sequencing

DNA methylation most commonly occurs as 5-methylcytosine (5-mC) in the human genome and has been associated with human diseases. Recent developments in single-molecule sequencing technologies (Oxford Nanopore Technologies (ONT) and Pacific Biosciences) have enabled readouts of long, native DNA molecules, including cytosine methylation. ONT recently upgraded their Nanopore sequencing chemistry and kits from R9 to the R10 version, which yielded increased accuracy and sequencing throughput. However the effects on methylation detection have not yet been documented. Here we performed a series of computational analyses to characterize differences in Nanopore-based 5mC detection between the ONT R9 and R10 chemistries. We compared 5mC calls in R9 and R10 for three human genome datasets: a cell line, a frontal cortex brain sample, and a blood sample. We performed an in-depth analysis on CpG islands and homopolymer regions, and documented high concordance for methylation detection among sequencing technologies. The strongest correlation was observed between Nanopore R10 and Illumina bisulfite technologies for cell line-derived datasets. Subtle differences in methylation datasets between technologies can impact analysis tools such as differential methylation calling software. Our findings show that comparisons can be drawn between methylation data from different Nanopore chemistries using guided hypotheses. This work will facilitate comparison among Nanopore data cohorts derived using different chemistries from large scale sequencing efforts, such as the NIH CARD Long Read Initiative.

genomics↗

bioRxiv2024

A 20-year time-series of a freshwater lake reveals seasonal dynamics and environmental drivers of viral diversity, ecology, and evolution

Long-term ecological studies are powerful tools to investigate microbiomes and ecosystem change but have mostly ignored viruses. Here, we leveraged a 20-year time-series of a freshwater lake to characterize 1.3 million viral genomes over time, seasonality, and environmental factors. We identified 578 auxiliary metabolic gene (AMG) clusters representing over 150,000 AMGs, the most abundant of which, including psbA for photosynthesis, pmoC for methane oxidation, and katG for hydrogen peroxide decomposition, were consistently represented in viruses across decades and seasons. We observed positive associations and niche differentiation between virus-host pairs during seasonal change including in keystone taxa, Cyanobacteria, methanotrophs, and Nanopelagicales. Environmental constraints, specifically inorganic carbon and ammonium influenced viral abundances over time, and highlighted roles of viruses in both "top-down" and "bottom-up" interactions. Key evolutionary processes shaping gene and genome-wide selection included favored fitness genes, reduced genomic heterogeneity, and dominant sub-populations carrying specific genes. Overall, our study advances understanding of diversity, ecological dynamics, and evolutionary trajectories of viruses in Earths microbiomes and ecosystems.

microbiology↗

bioRxiv2023

Matrix architecture and mechanics regulate myofibril organization, costamere assembly, and contractility of engineered myocardial microtissues

The mechanical function of the myocardium is defined by cardiomyocyte contractility and the biomechanics of the extracellular matrix (ECM). Understanding this relationship remains an important unmet challenge due to limitations in existing approaches for engineering myocardial tissue. Here, we established arrays of cardiac microtissues with tunable mechanics and architecture by integrating ECM-mimetic synthetic, fiber matrices and induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), enabling real-time contractility readouts, in-depth structural assessment, and tissue-specific computational modeling. We find that the stiffness and alignment of matrix fibers distinctly affect the structural development and contractile function of pure iPSC-CM tissues. Further examination into the impact of fibrous matrix stiffness enabled by computational models and quantitative immunofluorescence implicates cell-ECM interactions in myofibril assembly and notably costamere assembly, which correlates with improved contractile function of tissues. These results highlight how iPSC-CM tissue models with controllable architecture and mechanics can inform the design of translatable regenerative cardiac therapies.

bioengineering↗

bioRxiv2023

Sulfide oxidation promotes hypoxic angiogenesis and neovascularization

Angiogenic programming in the vascular endothelium is a tightly regulated process to maintain tissue homeostasis and is activated in tissue injury and the tumor microenvironment. The metabolic basis of how gas signaling molecules regulate angiogenesis is elusive. Herein, we report that hypoxic upregulation of NO synthesis in endothelial cells reprograms the transsulfuration pathway and increases H2S biogenesis. Furthermore, H2S oxidation by mitochondrial sulfide quinone oxidoreductase (SQOR) rather than downstream persulfides, synergizes with hypoxia to induce a reductive shift, limiting endothelial cell proliferation that is attenuated by dissipation of the mitochondrial NADH pool. Tumor xenografts in whole-body WBCreSQORfl/fl knockout mice exhibit lower mass and reduced angiogenesis compared to SQORfl/fl controls. WBCreSQORfl/fl mice also exhibit reduced muscle angiogenesis following femoral artery ligation, compared to controls. Collectively, our data reveal the molecular intersections between H2S, O2 and NO metabolism and identify SQOR inhibition as a metabolic vulnerability for endothelial cell proliferation and neovascularization. HighlightsO_LIHypoxic induction of *NO in endothelial cells inhibits CBS and switches CTH reaction specificity C_LIO_LIHypoxic interruption of the canonical transsulfuration pathway promotes H2S synthesis C_LIO_LISynergizing with hypoxia, SQOR deficiency induces a reductive shift in the ETC and restricts proliferation C_LIO_LISQOR KO mice exhibit lower neovascularization in tumor xenograft and hind limb ischemia models C_LI

biochemistry↗

bioRxiv2022

A Glass Phase Plate for Wavelength SensitiveSuperresolution Microscopy

Multicolor localization microscopy typically relies on sequential imaging and bandpass filters to distinguish fluorescent tags, which introduces temporal delays during live imaging, and decreases photon yield. By engineering the point-spread function (PSF), different fluors can be imaged simultaneously and distinguished by their unique patterns, without discarding photons. Here, we insert a silicon-dioxide phase plate at the Fourier plane of the detection path of a wide-field fluorescence microscope to produce distinguishable PSFs (X-PSFs) at different wavelengths. We demonstrate that the resulting PSFs can be localized spatially and spectrally using a statistics-based computational algorithm and can be utilized for hyper-spectral super-resolution microscopy of biological samples. Single PSFs in fixed U2OS cells were acquired using dSTORM with simultaneous illumination of fluors without emission filters. The modified PSF achieves [~]21 nm lateral localization precision (FWHM), [~]17 nm axial precision (FWHM) with an average of 1,800 - 3,500 photons per PSF and a background as high as 130 - 400 photons per pixel. The modified PSF can distinguish up to three fluorescent probes with [~]80 nm peak-to-peak separation between consecutive spectra.

biophysics↗

bioRxiv2021

Synthetic Natural Product-Inspired Peptides

Natural products (NPs) are a bountiful source of bioactive molecules. Unfortunately, discovery of novel bioactive NPs is challenging due to cryptic biosynthetic gene clusters (BGCs), low titers, and arduous purifications. Herein, we describe SNaPP (Synthetic Natural Product Inspired Peptides), a method for identifying NP-inspired bioactive molecules. SNaPP expedites bioactive molecule discovery by combining bioinformatics predictions of non-ribosomal peptide synthetases (NRPS) with chemical synthesis of the predicted NPs (pNPs). SNaPP utilizes a recently discovered cyclase, the penicillin binding protein (PBP)-like cyclase, as the lynchpin for the development of a library of cyclic peptide pNPs. Analysis of 500 BGCs allowed for identification of 131 novel pNPs. 51 diverse pNPs were synthesized using solid phase peptide synthesis and in-solution cyclization. Antibacterial testing revealed 14 pNPs with antibiotic activity, including activity against multidrug-resistant Gram-negative bacteria. Overall, SNaPP demonstrates the power of combining bioinformatics predictions with chemical synthesis to accelerate the discovery of bioactive molecules.

microbiology↗

bioRxiv2021

High-Stability Polyimide-based Flexible Electrodes with IrOx to Interface the Mouse Vagus Nerve

ObjectiveWe developed robust and cost-effective cuff Flex electrodes to facilitate bioelectronic medicine research in mouse models. They utilize polyimide (PI) as a dielectric insulation and iridium oxide (IrOx) for the electrodes, and are designed to interface small autonomic and somatic nerves (e.g. mouse vagus nerve). ApproachFlex electrodes were made using micro-fabrication technology, and innovative integration processes were developed to enable reliable acute and chronic vagus nerve interfaces. The electrochemical properties of Flex electrodes were characterized. Moreover, accelerated aging at 57 {degrees}C and stimulation-stability (Stim-Stab) testing (109 pulses at [~] 1.59 mC/cm2/phase) were performed to evaluate the lifetime of the PI encapsulation and IrOx electrodes, respectively. Flex electrodes efficacy was demonstrated by stimulating the mouse vagus nerve ([~]100 {micro}m) and measuring heart and respiratory rate changes as biomarkers. ResultsCost effective and robust lead and connector integration strategies were demonstrated, including small helical leads that improved the lead elongation by > 7x. PI encapsulation had stable impedance spectra for at least 336 days for interdigitated electrodes. Stim-Stab testing using an aggressive paradigm and rigorous optical and electrical characterization, revealed that half of electrodes showed less than minor damage at the endpoints. A trend of decreasing respiratory rate with stimulation current reached statistical significance at 500 {micro}A, demonstrating efficacy for Flex electrodes. SignificanceFlex electrodes offer demonstrated efficacy, low impedance (443 {+/-} 32 {Omega} at 103 Hz), excellent bench test stability, and cost-effective fabrication. Acute devices are easy to integrate, and mechanically robust chronic devices will be investigated in vivo in future studies. These characteristics make the electrodes well-positioned to advance bioelectronics medicine research by 1) enabling reliable studies with statistically relevant populations of acute mouse models, and 2) offering the potential for a technology that can be used in chronic studies, which scales to very small nerves.

bioengineering↗

bioRxiv2021

Individualized Spatial Network Predictions Using Siamese Convolutional Neural Networks: A Resting-State fMRI Study of over 11,000 Unaffected Individuals

Individuals can be characterized in a population according to their brain measurements and activity, given the inter-subject variability in brain anatomy, structure-function relationships, or life experience. Many neuroimaging studies have demonstrated the potential of functional network connectivity patterns estimated from resting functional magnetic resonance imaging (fMRI) to discriminate groups and predict information about individual subjects. However, the predictive signal present in the spatial heterogeneity of brain connectivity networks is yet to be extensively studied. In this study, we investigate, for the first time, the use of pairwise-relationships between resting-state independent spatial maps to characterize individuals. To do this, we develop a deep Siamese framework comprising three-dimensional convolution neural networks for contrastive learning based on individual-level spatial maps estimated via a fully automated fMRI independent component analysis approach. The proposed framework evaluates whether pairs of spatial networks (e.g., visual network and auditory network) are capable of subject identification and assesses the spatial variability in different network pairs predictive power in an extensive whole-brain analysis. Our analysis on nearly 12,000 unaffected individuals from the UK Biobank study demonstrates that the proposed approach can discriminate subjects with an accuracy of up to 88% for a single network pair on the test set (best model, after several runs), and 82% average accuracy at the subcortical domain level, notably the highest average domain level accuracy attained. Further investigation of our networks learned features revealed a higher spatial variability in predictive accuracy among younger brains and significantly higher discriminative power among males. In sum, the relationship among spatial networks appears to be both informative and discriminative of individuals and should be studied further as putative brain-based biomarkers.

neuroscience↗

bioRxiv2021

Genetic Basis of Variation in Cocaine and Methamphetamine Consumption in Outbred Populations of Drosophila melanogaster

We used Drosophila melanogaster to map the genetic basis of naturally occurring variation in voluntary consumption of cocaine and methamphetamine. We derived an outbred advanced intercross population (AIP) from 37 sequenced inbred wild-derived lines of the Drosophila melanogaster Genetic Reference Panel (DGRP), which are maximally genetically divergent, have minimal residual heterozygosity, are not segregating for common inversions, and are not infected with Wolbachia pipientis. We assessed consumption of sucrose, methamphetamine-supplemented sucrose and cocaine-supplemented sucrose, and found considerable phenotypic variation for consumption of both drugs, in both sexes. We performed whole genome sequencing and extreme QTL mapping on the top 10% of consumers for each replicate, sex and condition, and an equal number of randomly selected flies. We evaluated changes in allele frequencies among high consumers and control flies and identified 3,033 variants significantly (P < 1.9 x 10-8) associated with increased consumption, located in or near 1,962 genes. Many of these genes are associated with nervous system development and function, and 77 belong to a known gene-gene interaction subnetwork. We assessed the effects of RNA interference (RNAi) on drug consumption for 22 candidate genes; 17 had a significant effect in at least one sex. We constructed allele-specific AIPs which were homozygous for alternative candidate alleles for 10 SNPs and measured average consumption for each population; nine SNPs had significant effects in at least one sex. The genetic basis of voluntary drug consumption in Drosophila is polygenic and implicates genes with human orthologs and associated variants with sex- and drug-specific effects. Significance StatementThe use of cocaine and methamphetamine presents significant socioeconomic problems. However, identifying the genetic underpinnings that determine susceptibility to substance use is challenging in human populations. The fruit fly, Drosophila melanogaster, presents a powerful genetic model since we can control the genetic background and environment, 75% of disease-causing genes in humans have a fly counterpart, and flies - like humans - exhibit adverse effects upon cocaine and methamphetamine exposure. We showed that the genetic architecture underlying variation in voluntary cocaine and methamphetamine consumption differs between sexes and is dominated by variants in genes associated with connectivity and function of the nervous system. Results obtained from the Drosophila gene discovery model can guide studies on substance abuse susceptibility in human populations.

genetics↗

bioRxiv2019

2′-5′-Oligoadenylate synthetase-like protein inhibits intracellular M. tuberculosis replication and promotes proinflammatory cytokine secretion

Host cytoplasmic surveillance pathways are known to elicit type I interferon (IFN) responses which are crucial to antimicrobial defense mechanisms. Oligoadenylate synthetase-like (OASL) protein has been extensively characterized as a part of the anti-viral mechanism, however a number of transcriptomic studies reveal its upregulation in response to infection with a wide variety of intracellular bacterial pathogens. To date, there is no evidence documenting the role (if any) of OASL during mycobacterium tuberculosis infection. Using two pathogenic strains differing in virulence only, as well as the non-pathogenic M. bovis BCG strain, we observed that pathogenicity and virulence strongly induced OASL expression after 24 h of infection. Further, we observed that OASL knock down led to a significant increase in M. tb CFU counts 96 h post-infection in comparison to the respective controls. Luminex revealed that OASL silencing significantly decreased IL-1{beta}, TNF- and MCP-1 secretion in THP-1 cells and had no effect on IL-10 secretion. We therefore postulate that OASL regulates pro-inflammatory mediators such as cytokines and chemokines which suppress intracellular mycobacterial growth and survival.

cell biology↗

bioRxiv2019

Analytical characterization of Parylene-C degradation mechanisms on Utah arrays: evaluation of in vitro Reactive Accelerated Aging model compared to multiyear in vivo implantation

Implantable neural microelectrodes are integral components of neuroprosthetic technologies and can transform treatments for many neural-mediated disorders. However, dielectric material degradation during long-term (> 1 year) indwelling periods restricts device functional lifetimes to a few years. This comprehensive work carefully investigates in vivo material degradation and also explores the ability of in vitro Reactive Accelerated Aging (RAA) to evaluate implant stability. Parylene C-coated Utah electrode arrays (UEAs) implanted in feline peripheral nerve for 3.25 years were explanted and compared to RAA-processed devices, aged in phosphate buffered saline (PBS) + 20 mM H2O2 at either 67 or 87 {degrees}C (28 or 7 days, respectively). Electron microscopy revealed similar physical damage characteristics between explants and RAA (87{degrees} C) devices. Parylene C degradation was overwhelmingly apparent for UEAs from both RAA cohorts. Controls aged in PBS alone displayed almost no damage. Spectroscopic characterization (EDX, XPS, FTIR) found clear indications of oxidation and chlorine abstraction for parylene C aged in vivo. While in vitro aging was also accompanied by signs of oxidation, changes in the chemistry in vivo and in vitro were statistically different. Analysis of RAA- aged devices identified UEA fabrication approaches that may greatly improve device resistance to degradation. This work underscores the need for an improved understanding of in vivo damage mechanisms, to facilitate the critical need for representative in vitro accelerated testing paradigms for long-term implants.

bioengineering↗

bioRxiv2018

Genetics of Cocaine and Methamphetamine Consumption and Preference in Drosophila melanogaster

Illicit use of psychostimulants, such as cocaine and methamphetamine, constitutes a significant public health problem. Whereas neural mechanisms that mediate the effects of these drugs are well-characterized, genetic factors that account for individual variation in susceptibility to substance abuse and addiction remain largely unknown. Drosophila melanogaster can serve as a translational model for studies on substance abuse, since flies have a dopamine transporter that can bind cocaine and methamphetamine, and exposure to these compounds elicits effects similar to those observed in people, suggesting conserved evolutionary mechanisms underlying drug responses. Here, we used the D. melanogaster Genetic Reference Panel to investigate the genetic basis for variation in psychostimulant drug consumption, to determine whether similar or distinct genetic networks underlie variation in consumption of cocaine and methamphetamine, and to assess the extent of sexual dimorphism and effect of genetic context on variation in voluntary drug consumption. Quantification of natural genetic variation in voluntary consumption, preference, and change in consumption and preference over time for cocaine and methamphetamine uncovered significant genetic variation for all traits, including sex-, exposure-and drug-specific genetic variation. Genome wide association analyses identified both shared and drug-specific candidate genes, which could be integrated in genetic interaction networks. We assessed the effects of ubiquitous RNA interference (RNAi) on consumption behaviors for 34 candidate genes: all affected at least one behavior. Finally, we utilized RNAi knockdown in the nervous system to implicate dopaminergic neurons and the mushroom bodies as part of the neural circuitry underlying experience-dependent development of drug preference.\n\nAUTHOR SUMMARYIllicit use of cocaine and methamphetamine is a major public health problem. Whereas the neurological effects of these drugs are well characterized, it remains challenging to determine genetic risk factors for substance abuse in human populations. The fruit fly, Drosophila melanogaster, presents an excellent model for identifying evolutionarily conserved genes that affect drug consumption, since genetic background and exposure can be controlled precisely. We took advantage of natural variation in a panel of inbred wild derived fly lines with complete genome sequences to assess the extent of genetic variation among these lines for voluntary consumption of cocaine and methamphetamine and to explore whether some genetic backgrounds might show experience-dependent development of drug preference. The drug consumption traits were highly variable among the lines with strong sex-, drug- and exposure time-specific components. We identified candidate genes and gene networks associated with variation in consumption of cocaine and methamphetamine and development of drug preference. Using tissue-specific suppression of gene expression, we were able to functionally implicate candidate genes that affected at least one consumption trait in at least one drug and sex. In humans, the mesolimbic dopaminergic projection plays a role in drug addiction. We asked whether in Drosophila the mushroom bodies could play an analogous role, as they are integrative brain centers associated with experience-dependent learning. Indeed, our results suggest that variation in consumption and development of preference for both cocaine and methamphetamine is mediated, at least in part, through a neural network that comprises dopaminergic projections to the mushroom bodies.

genomics↗