Biology subjects

Johnson, D.

Publications and source records attributed to Johnson, D..

8 recordsLinked to original sources

bioRxiv2026

Persistent but variable effect of experimental laboratory burns on microbial community resistance, resilience, and function across contrasting boreal forest soils

Boreal forests stretch across vast swaths of the northern hemisphere, are shaped by wildfire, and play an important role in the global carbon cycle. Microorganisms play a critical role in soil nutrient cycling in these ecosystems, yet there are many open questions about the impacts of wildfire on microbially mediated soil biogeochemical cycles. In this study, we used laboratory burns and soil incubations of intact soil cores collected from two distinct soil types -- Histosols and Gleysols -- from boreal forest within Wood Buffalo National Park, Alberta, Canada, to assess burn effects on soil bacterial and fungal community composition and function. We compared resistance and resilience to burning for microbial communities vs. resistance and resilience to burning for soil pH and soil respiration to assess the relationships between burn-induced shifts in microbial community composition, the soil environment, and microbial activity. To link shifts in microbial community composition to potential community function, we measured glucose-specific carbon use efficiency (CUE) and assessed its relationship with weighted mean predicted 16S rRNA gene copy numbers for bacterial communities and FUNGuild-estimated relative abundance of putative symbiotrophic and saprotrophic fungi in burned and unburned soils. Microbial community resistance and resilience to burning varied across soil type with higher resistance of both bacterial and fungal communities from Histosols compared to the O horizons of Gleysols. This may be explained by a larger impact of burning on microbes in the thinner Gleysol O horizons. The relatively low resilience of bacterial and fungal communities to burning as well as the failure of resilience to increase with time since burning supports previous reports of post-burn microbial community recovery occurring over years rather than months. Burning caused a decrease in CUE with larger decreases following longer, hotter burns, which correlated with an increase in weighted mean predicted 16S rRNA gene copy number, raising the possibility that copy number could serve as a proxy for post-fire CUE in boreal forest soils, though more research is needed to constrain the effects of environmental conditions, substrates, and time since fire on this relationship. These findings suggest several ways in which burn-induced shifts in microbial community composition reflect altered microbial community function in meaningful ways for soil carbon cycling.

ecology↗

bioRxiv2018

PhenoMeNal: Processing and analysis of Metabolomics data in the Cloud

BackgroundMetabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organisms metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological and many other applied biological domains. Its computationally-intensive nature has driven requirements for open data formats, data repositories and data analysis tools. However, the rapid progress has resulted in a mosaic of independent - and sometimes incompatible - analysis methods that are difficult to connect into a useful and complete data analysis solution.\n\nFindingsThe PhenoMeNal (Phenome and Metabolome aNalysis) e-infrastructure provides a complete, workflow-oriented, interoperable metabolomics data analysis solution for a modern infrastructure-as-a-service (IaaS) cloud platform. PhenoMeNal seamlessly integrates a wide array of existing open source tools which are tested and packaged as Docker containers through the projects continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardized, automated and published analysis workflows in the user interfaces Galaxy, Jupyter, Luigi and Pachyderm.\n\nConclusionsPhenoMeNal constitutes a keystone solution in cloud infrastructures available for metabolomics. It provides scientists with a ready-to-use, workflow-driven, reproducible and shareable data analysis platform harmonizing the software installation and configuration through user-friendly web interfaces. The deployed cloud environments can be dynamically scaled to enable large-scale analyses which are interfaced through standard data formats, versioned, and have been tested for reproducibility and interoperability. The flexible implementation of PhenoMeNal allows easy adaptation of the infrastructure to other application areas and omics research domains.

bioinformatics↗

bioRxiv2018

Measuring Illumina Size Bias Using REcount: A Novel Method for Highly Accurate Quantification of Engineered Genetic Constructs

Quantification of DNA sequence tags associated with engineered genetic constructs underlies many genomics measurements. Typically, such measurements are done using PCR to enrich sequence tags and add adapters, followed by next-generation sequencing (NGS). However, PCR amplification can introduce significant quantitative error into these measurements. Here we describe REcount, a novel PCR-free direct counting method for NGS-based quantification of engineered genetic constructs. By comparing measurements of defined plasmid pools to droplet digital PCR data, we demonstrate that this method is highly accurate and reproducible. We further demonstrate that the REcount approach is amenable to multiplexing through the use of orthogonal restriction enzymes. Finally, we use REcount to provide new insights into clustering biases due to molecule length across different Illumina sequencing platforms.

genomics↗

bioRxiv2018

Population sequencing reveals clonal diversity and ancestral inbreeding in the grapevine cultivar Chardonnay

Chardonnay is the basis of some of the worlds most iconic wines and its success is underpinned by a historic program of clonal selection. There are numerous clones of Chardonnay available that exhibit differences in key viticultural and oenological traits that have arisen from the accumulation of somatic mutations during centuries of asexual propagation. However, the genetic variation that underlies these differences remains largely unknown. To address this knowledge gap, a high-quality, diploid-phased Chardonnay genome assembly was produced from single-molecule real time sequencing, and combined with re-sequencing data from 15 different commercial Chardonnay clones. There were 1620 markers identified that distinguish the 15 Chardonnay clones. These markers were reliably used for clonal identification of validation genomic material, as well as in identifying a potential genetic basis for some clonal phenotypic differences. The predicted parentage of the Chardonnay haplomes was elucidated by mapping sequence data from the predicted parents of Chardonnay (Gouais blanc and Pinot noir) against the Chardonnay reference genome. This enabled the detection of instances of heterosis, with differentially-expanded gene families being inherited from the parents of Chardonnay. Most surprisingly however, the patterns of nucleotide variation present in the Chardonnay genome indicate that Pinot noir and Gouais blanc share an extremely high degree of kinship that has resulted in the Chardonnay genome displaying characteristics that are indicative of inbreeding.\n\nAuthor SummaryPhenotypic variation within a grapevine cultivar arises from an accumulation of mutations from serial vegetative propagation. Old cultivars such as Chardonnay have been propagated for centuries resulting in hundreds of available clones containing unique genetic mutations and a range of various phenotypic peculiarities. The genetic mutations can be leveraged as genetic markers and are useful in identifying specific clones for authenticity testing, or as breeding markers for new clonal selections where particular mutations are known to confer a phenotypic trait. We produced a high-quality genome assembly for Chardonnay, and using re-sequencing data for 15 popular clones, were able to identify a large selection of markers that are unique to at least one clone. We identified mutations that may confer phenotypic effects, and were able to identify clones from material independently sourced from nurseries and vineyards. The marker detection framework we describe for authenticity testing would be applicable to other grapevine cultivars or even other agriculturally important woody-plant crops that are vegetatively propagated such as fruit orchards. Finally, we show that the Chardonnay genome contains extensive evidence for parental inbreeding, such that its parents, Gouais blanc and Pinot noir, may even represent first-degree relatives.

genomics↗

bioRxiv2018

The Nucleome of Developing Murine Rod Photoreceptors

The nuclei of rod photoreceptors in mice and other nocturnal species have an unusual inverted chromatin structure: the heterochromatin is centrally located to help focus light and improve photosensitivity. To better understand this unique nuclear organization, we performed ultra-deep Hi-C analysis on murine retina at 3 stages of development and on purified rod photoreceptors. Predicted looping interactions from the Hi-C data were validated with fluorescence in situ hybridization (FISH). We discovered that a subset of retinal genes that are important for retinal development, cancer, and stress response are localized to the facultative heterochromatin domain. We also used machine learning to develop an algorithm based on our chromatin Hidden Markov Modeling (chromHMM) of retinal development to predict heterochromatin domains and study their dynamics during retinogenesis. FISH data for 264 genomic loci were used to train and validate the algorithm. The integrated data were then used to identify a developmental stage- and cell type-specific core regulatory circuit super-enhancer (CRC-SE) upstream of the Vsx2 gene, which is required for bipolar neuron expression. Deletion of the Vsx2 CRC-SE in mice led to the loss of bipolar neurons in the retina.

neuroscience↗

bioRxiv2018

Stepwise C-Terminal Truncation of Cardiac Troponin T Alters Function at Low and Saturating Ca2+

Activation of striated muscle contraction occurs in response to Ca2+ binding to troponin C (TnC). The resulting reorganization of troponin repositions tropomyosin on actin and permits activation of myosin catalyzed ATP hydrolysis. It now appears that the levels of activity at both low and saturating Ca2+ are modulated by the C-terminal 14 amino acids of cardiac troponin T (TnT). We made a series of mutants of human cardiac troponin T, isoform 2, with deletions from the C-terminal end: {Delta}4, {Delta}6, {Delta}8, {Delta}10 and {Delta}14. We measured the effect of these mutations on the normalized ATPase activity at saturating Ca2+, the change in acrylodan tropomyosin fluorescence at low Ca2+, and the degree of Ca2+ stimulation of the rate of binding of rigor myosin S1 to pyrene-labeled actin-tropomyosin-troponin. Together, these measurements define the distribution of actin-tropomyosin-troponin among the 3 regulatory states. Results from rates of rigor S1 binding deviated from other measurements when > 8 residues of TnT were deleted. That deviation was due to increased rates of binding of rigor S1 to pyrene-labeled actin with truncated TnT at saturating Ca2+. Such behavior violated a key assumption in the determination of the B state by this method. Nevertheless, all methods show that as residues were removed from the C-terminus of TnT there was approximately a proportional loss of the inactive B state at low Ca2+ and an increase in the active M state at saturating Ca2+. Most of the C-terminal 14 residues of human cardiac troponin T are essential for forming the inactive B state at low Ca2+ and for limiting the formation of the active M state at saturating Ca2+.

biochemistry↗

bioRxiv2017

Interoperable and scalable metabolomics data analysis with microservices

Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed in parallel using the Kubernetes container orchestrator. The access point is a virtual research environment which can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and established workflows can be re-used effortlessly by any novice user. We validate our method in the field of metabolomics on two mass spectrometry studies, one nuclear magnetic resonance spectroscopy study and one fluxomics study, showing that the method scales dynamically with increasing availability of computational resources. We achieved a complete integration of the major software suites resulting in the first turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, multivariate statistics, and metabolite identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative science.

bioinformatics↗

bioRxiv2017

Reflected stochastic differential equation models for constrained animal movement

Movement for many animal species is constrained in space by barriers such as rivers, shore-lines, or impassable cliffs. We develop an approach for modeling animal movement constrained in space by considering a class of constrained stochastic processes, reflected stochastic differential equations. Our approach generalizes existing methods for modeling unconstrained animal movement. We present methods for simulation and inference based on augmenting the constrained movement path with a latent unconstrained path and illustrate this augmentation with a simulation example and an analysis of telemetry data from a Steller sea lion (Eumatopias jubatus) in southeast Alaska.

animal behavior and cognition↗