Biology subjects

Davis, S.

Publications and source records attributed to Davis, S..

66 records · Page 4Linked to original sources

bioRxiv2019

Prevalent pH controls the capacity of Galdieria maxima to use ammonia and nitrate as a nitrogen source.

Galdieria maxima is a polyextremophilic alga capable of diverse metabolic processes. Ammonia is widely used in culture media typical of laboratory growth. Recent reports that this species can grow on wastes promote the concept that G. maxima might have biotechnological utility. Accordingly, there is a need to know the range of pH levels that can support G. maxima growth in a given nitrogen source. Here, we examined the combined effect of pH and nitrate/ammonium source on the growth and long-term response of the photochemical process to a pH gradient in different G. maxima strains. All were able to use differing nitrogen sources, despite both the growth rate and photochemical activity were significantly affected by the combination with the pH. All strains acidified the NH4+-medium (pH<3); only G. maxima IPPAS P507 showed reduced capacity in lowering the pH from 6.5. pH was a limiting factor in nitrate uptake at pH[≥]6.5; noteworthy, at pH 5 on nitrate G. maxima ACUF551 showed a good growth performance, despite the alkalization of the medium.

plant biology↗

bioRxiv2019

The mitochondrial Ca2+ uniporter MCU is required for normal glucose-stimulated insulin secretion in vitro and in vivo

Mitochondrial oxidative metabolism is central to glucose-stimulated insulin secretion (GSIS). Whether Ca2+ uptake into pancreatic {beta}-cell mitochondria potentiates or antagonises this process is still a matter of debate. Although the mitochondrial importer (MCU) complex is thought to represent the main route for Ca2+ transport across the inner mitochondrial membrane, its role in {beta}-cells has not previously been examined in vivo. Here, we inactivated the pore-forming subunit MCUa (MCU) selectively in the {beta}-cell in mice using Ins1Cre-mediated recombination. Glucose-stimulated mitochondrial Ca2+ accumulation, ATP production and insulin secretion were strongly (p<0.05 and p<0.01) inhibited in MCU null animals ({beta}MCU-KO) in vitro. Interestingly, cytosolic Ca2+ concentrations increased (p<0.001) whereas mitochondrial membrane depolarisation improved in {beta}MCU-KO animals. Male {beta}MCU-KO mice displayed impaired in vivo insulin secretion at 5 (p<0.001) but not 15 min. post intraperitoneal (IP) injection of glucose while the opposite phenomenon was observed following an oral gavage at 5 min. Unexpectedly, glucose tolerance was improved (p<0.05) in young {beta}MCU-KO (<12 weeks), but not older animals. We conclude that MCU is crucial for mitochondrial Ca2+ uptake in pancreatic {beta}-cells and is required for normal GSIS. The apparent compensatory mechanisms which maintain glucose tolerance in {beta}MCU-KO mice remain to be established.

physiology↗

bioRxiv2019

Melanoblast transcriptome analysis reveals novel pathways promoting melanoma metastasis

Cutaneous malignant melanoma is an aggressive cancer of melanocytes with a strong propensity to metastasize. We posited that melanoma cells acquire metastatic capability by adopting an embryonic-like phenotype, and that a lineage approach would uncover novel metastatic melanoma biology. We used a genetically engineered mouse model to generate a rich melanoblast transcriptome dataset, identified melanoblast-specific genes whose expression contributed to metastatic competence, and derived a 43-gene signature that predicted patient survival. We identified a melanoblast gene, KDELR3, whose loss impaired experimental metastasis. In contrast, KDELR1 deficiency enhanced metastasis, providing the first example of different disease etiologies within the KDELR-family of retrograde transporters. We show that KDELR3 regulates the metastasis suppressor, KAI1, and report an interaction with the E3 ubiquitin-protein ligase gp78, a regulator of KAI1 degradation. Our work demonstrates that the melanoblast transcriptome can be mined to uncover novel targetable pathways for melanoma therapy.

cancer biology↗

bioRxiv2019

Towards a gold standard for benchmarking gene set enrichment analysis

BackgroundAlthough gene set enrichment analysis has become an integral part of high-throughput gene expression data analysis, the assessment of enrichment methods remains rudimentary and ad hoc. In the absence of suitable gold standards, evaluations are commonly restricted to selected data sets and biological reasoning on the relevance of resulting enriched gene sets. However, this is typically incomplete and biased towards the goals of individual investigations.\n\nResultsWe present a general framework for standardized and structured benchmarking of enrichment methods based on defined criteria for applicability, gene set prioritization, and detection of relevant processes. This framework incorporates a curated compendium of 75 expression data sets investigating 42 different human diseases. The compendium features microarray and RNA-seq measurements, and each dataset is associated with a precompiled GO/KEGG relevance ranking for the corresponding disease under investigation. We perform a comprehensive assessment of 10 major enrichment methods on the benchmark compendium, identifying significant differences in (i) runtime and applicability to RNA-seq data, (ii) fraction of enriched gene sets depending on the type of null hypothesis tested, and (iii) recovery of the a priori defined relevance rankings. Based on these findings, we make practical recommendations on (i) how methods originally developed for microarray data can efficiently be applied to RNA-seq data, (ii) how to interpret results depending on the type of gene set test conducted, and (iii) which methods are best suited to effectively prioritize gene sets with high relevance for the phenotype investigated.\n\nConclusionWe carried out a systematic assessment of existing enrichment methods, and identified best performing methods, but also general shortcomings in how gene set analysis is currently conducted. We provide a directly executable benchmark system for straightforward assessment of additional enrichment methods.\n\nAvailabilityhttp://bioconductor.org/packages/GSEABenchmarkeR

bioinformatics↗

bioRxiv2019

Neural correlates of cardiac interoceptive accuracy across development: implications for social symptoms in autism spectrum disorders

BackgroundInteroception involves the processing of sensory information relevant to physiological functioning and is integral to building self-awareness, emotional states, and modulating social behaviors. With the role of interoception in emotional processing and social functioning, there is growing interest in characterizing interoception in autism spectrum disorder (ASD), yet, there are mixed results regarding cardiac interoceptive accuracy in ASD.\n\nMethodsIn this study, we explored the neural basis of cardiac interoception using an fMRI heartbeat counting task in order to assess neural correlates of primary interoception. We predicted that interoceptive-specific response in the insula, a \"hub\" for interoception, would be related to ASD symptomatology. We investigated the relationship of insula responses during cardiac interoceptive accuracy and a self/caregiver-reported autism-related symptom scale (Social Responsiveness Scale-2 (SRS)). Participants included 46 individuals with autism spectrum disorder (ASD) (age 8-54, mean= 19.43{+/-}10.68 years) and 54 individuals with typical development for comparison (TC, age 8-53, mean= 21.43{+/-}10.41 years).\n\nResultsWe found no significant difference in cardiac interoceptive accuracy or neural response to cardiac interoception in ASD. Several insula sudivisons had a curvilinear relationship to age, peaking in early adulthood. Interoceptive-specific insula response was associated with adult self-report SRS scores; this association differed by diagnostic group and self/other report.\n\nConclusionsThis work suggests that 1) there is no global deficit in interoception in ASD, but that integrating interoceptive cues with social information may distinguish individuals with ASD, and 2) there is a developmental trajectory for interoceptive processing in the insula that may be relevant for socio-emotional health.

neuroscience↗

bioRxiv2019

recount-brain: a curated repository of human brain RNA-seq datasets metadata

The usability of publicly-available gene expression data is often limited by the availability of high-quality, standardized biological phenotype and experimental condition information (\"metadata\"). We released the recount2 project, which involved re-processing [~]70,000 samples in the Sequencing Read Archive (SRA), Genotype-Tissue Expression (GTEx), and The Cancer Genome Atlas (TCGA) projects. While samples from the latter two projects are well-characterized with extensive metadata, the [~]50,000 RNA-seq samples from SRA in recount2 are inconsistently annotated with metadata. Tissue type, sex, and library type can be estimated from the RNA sequencing (RNA-seq) data itself. However, more detailed and harder to predict metadata, like age and diagnosis, must ideally be provided by labs that deposit the data.\n\nTo facilitate more analyses within human brain tissue data, we have complemented phenotype predictions by manually constructing a uniformly-curated database of public RNA-seq samples present in SRA and recount2. We describe the reproducible curation process for constructing recount-brain that involves systematic review of the primary manuscript, which can serve as a guide to annotate other studies and tissues. We further expanded recount-brain by merging it with GTEx and TCGA brain samples as well as linking to controlled vocabulary terms for tissue, Brodmann area and disease. Furthermore, we illustrate how to integrate the sample metadata in recount-brain with the gene expression data in recount2 to perform differential expression analysis. We then provide three analysis examples involving modeling postmortem interval, glioblastoma, and meta-analyses across GTEx and TCGA. Overall, recount-brain facilitates expression analyses and improves their reproducibility as individual researchers do not have to manually curate the sample metadata. recount-brain is available via the add_metadata() function from the recount Bioconductor package at bioconductor.org/packages/recount.

genomics↗

bioRxiv2018

Molecular determinants of enterotoxigenic Escherichia coli heat-stable toxin secretion and delivery

Enterotoxigenic Escherichia coli (ETEC), a heterogeneous diarrheal pathovar defined by production of heat-labile (LT) and/or heat-stable (ST) toxins, remain major causes of mortality among children in developing regions, and cause substantial morbidity in individuals living in or traveling to endemic areas. Studies demonstrating a major burden of ST-producing ETEC have focused interest on ST toxoids for ETEC vaccines. We therefore examined fundamental aspects of ETEC ST biology using ETEC H10407, which carries estH and estP genes encoding ST-H and ST-P, respectively, in addition to eltAB genes responsible for LT. In this background, we found that deletion of estH significantly diminished cGMP activation in target epithelia, while deletion of estP had a surprisingly modest impact, and a dual estH/estP mutant was not appreciably different than the estH mutant. Nevertheless, either ST-H or ST-P recombinant peptides stimulated cGMP production. We also found that the TolC efflux protein was essential for both toxin secretion and delivery, providing a potential avenue for efflux inhibitors in treatment of acute diarrheal illness. In addition, we demonstrated that the EtpA adhesin is required for optimal delivery of ST and that antibodies against either the adhesin or ST-H significantly impaired toxin delivery and cGMP activation in target T84 cells. Finally, we used FLAG epitope fusions to demonstrate that the ST-H pro-peptide sequence is secreted by the bacteria, potentially providing additional targets for antibody neutralization. These studies collectively extend our understanding of ETEC pathogenesis and potentially inform additional avenues to mitigate disease by these common diarrheal pathogens.

microbiology↗

bioRxiv2018

Hydrophobicity drives the systemic distribution of lipid-conjugated siRNAs via lipid transport pathways

Efficient delivery of therapeutic RNA is the fundamental obstacle preventing its clinical utility. Lipid conjugation improves plasma half-life, tissue accumulation, and cellular uptake of small interfering RNAs (siRNAs). However, the impact of conjugate structure and hydrophobicity on siRNA pharmacokinetics is unclear, impeding the design of clinically relevant lipid-siRNAs. Using a panel of biologically-occurring lipids, we show that lipid conjugation modulates siRNA hydrophobicity and governs spontaneous partitioning into distinct plasma lipoprotein classes in vivo. Lipoprotein binding influences siRNA distribution by delaying renal excretion and promoting uptake into lipoprotein receptor-enriched tissues. Lipid-siRNAs elicit mRNA silencing without causing toxicity in a tissue-specific manner. Lipid-siRNA internalization occurs independently of lipoprotein endocytosis, and is mediated by siRNA phosphorothioate modifications. Although biomimetic lipoprotein nanoparticles have been considered for the enhancement of siRNA delivery, our findings suggest that hydrophobic modifications can be leveraged to incorporate therapeutic siRNA into endogenous lipid transport pathways without the requirement for synthetic formulation.

pharmacology and toxicology↗

bioRxiv2018

Developmental genetics in a complex adaptive structure, the weevil rostrum

The rostrum of weevils (Curculionidae) is a novel, complex, adaptive structure that has enabled this huge beetle radiation to feed on and oviposit in a wide spectrum of plant hosts, correlated with diverse life histories and tremendous disparity in rostrum forms. In order to understand the development and evolution of this structure, transcriptomes were produced in de novo assemblies from the developing pre-pupal head tissues of two distantly related curculionids, the rice weevil (Sitophilus oryzae) and the mountain pine beetle (Dendroctonus ponderosae), which have highly divergent rostra. While there are challenges in assessing differences among transcriptomes and in relative gene expression from divergent taxa, tests for differential expression patterns of transcripts yielded lists of candidate genes to examine in future work. RNA interference was performed with S. oryzae for functional insight into the Hox gene Sex combs reduced. Scr has a conserved function in labial and prothoracic identities, but it also demonstrates a novel role in reduction of ventral head structures, namely the gula, submentum, and associated sulci, in weevils. Ultimately, this study makes strides towards elucidating how the weevil rostrum initially formed and the profound phenotypic diversity it has acquired throughout the curculionoid lineages. It furthermore initiates a better understanding of the genetic framework that permitted the diversification of such an immense lineage as the weevils.\n\nSummary statementThis study begins exploring the development of a novel, complex structure in one of the largest families of organisms, the weevils.

developmental biology↗

bioRxiv2017

Detecting pathogen exposure during the non-symptomatic incubation period using physiological data

Early pathogen exposure detection allows better patient care and faster implementation of public health measures (patient isolation, contact tracing). Existing exposure detection most frequently relies on overt clinical symptoms, namely fever, during the infectious prodromal period. We have developed a robust machine learning based method to better detect asymptomatic states during the incubation period using subtle, sub-clinical physiological markers. Starting with high-resolution physiological waveform data from non-human primate studies of viral (Ebola, Marburg, Lassa, and Nipah viruses) and bacterial (Y. pestis) exposure, we processed the data to reduce short-term variability and normalize diurnal variations, then provided these to a supervised random forest classification algorithm and post-classifier declaration logic step to reduce false alarms. In most subjects detection is achieved well before the onset of fever; subject cross-validation across exposure studies (varying viruses, exposure routes, animal species, and target dose) lead to 51h mean early detection (at 0.93 area under the receiver-operating characteristic curve [AUCROC]). Evaluating the algorithm against entirely independent datasets for Lassa, Nipah, and Y. pestis exposures un-used in algorithm training and development yields a mean 51h early warning time (at AUCROC=0.95). We discuss which physiological indicators are most informative for early detection and options for extending this capability to limited datasets such as those available from wearable, non-invasive, ECG-based sensors.

physiology↗

bioRxiv2017

Hox-logic of preadaptations for social insect symbiosis in rove beetles

How symbiotic lifestyles evolve from free-living ecologies is poorly understood. In Metazoas largest family, Staphylinidae (rove beetles), numerous lineages have evolved obligate behavioral symbioses with ants or termites. Widespread convergence of this lifestyle is thought to stem from a novel, chemically defended body plan that enables free-living species to infiltrate colonies and undergo extreme evolutionary specialization. Here we show how this innovative body plan evolved, via new Hox functions in staphylinids that remodeled the coleopteran groundplan. Using a model staphylinid, Dalotia coriaria, we reveal the Hox basis for changes in thoracic appendage morphology that shortened the beetle elytron and left the abdomen physically unprotected, selecting for an abdominal defense gland that was likely key to unlocking ant and termite societies. We present evidence that the gland evolved through a novel, combinatorial role of the abdominal Hox proteins AbdA and AbdB. These proteins function together to specify distinct gland cell types in neighboring segmental compartments, each cell type synthesizing a different class of compound--irritant, ester and solvent. Only when secreted together do these compounds constitute a bioactive secretion, providing an example of emergent chemical functionality that arises from synergy between individual gland cell types. Hox-controlled specification of glandular diversity implies a modularity in compound biosynthesis that likely catalyzed the evolvability of rove beetle chemistry, including the capacity of symbiotic taxa to produce potent compounds for host deception. This study reveals how Hox-controlled body axis modifications predispose a major animal to convergently evolve into symbionts.

evolutionary biology↗

bioRxiv2017

Software For The Integration Of Multi-Omics Experiments In Bioconductor

Multi-omics experiments are increasingly commonplace in biomedical research, and add layers of complexity to experimental design, data integration, and analysis. R and Bioconductor provide a generic framework for statistical analysis and visualization, as well as specialized data classes for a variety of high-throughput data types, but methods are lacking for integrative analysis of multi-omics experiments. The MultiAssayExperiment software package, implemented in R and leveraging Bioconductor software and design principles, provides for the coordinated representation of, storage of, and operation on multiple diverse genomics data. We provide all of the multiple omics data for each cancer tissue in The Cancer Genome Atlas (TCGA) as ready-to-analyze MultiAssayExperiment objects, and demonstrate in these and other datasets how the software simplifies data representation, statistical analysis, and visualization. The MultiAssayExperiment Bioconductor package reduces major obstacles to efficient, scalable and reproducible statistical analysis of multi-omics data and enhances data science applications of multiple omics datasets.

bioinformatics↗