Requirement of Dynactin p150Glued Subunit for the Functional Integrity of the Keratinocyte Microparasol

The keratinocyte microparasol, composed of a perinuclear microtubular/melano–phagolysosomal complex, protects the nucleus from UV-induced DNA damage. We have previously demonstrated that cytoplasmic dynein is the motor involved in the perinuclear-directed aggregation of phagocytosed melanosomes. Dynactin, of which p150Glued is the major subunit, can link directly to microtubules and links organelles to dynein at different domains. To further define the mechanism of the microparasol, we transfected siRNA targeted against p150Glued into human keratinocytes cultured with 0.5mm fluorescent microspheres and performed time-lapse analysis, confocal immunolocalization, and Western immunoblotting after 24 and 48 hours. Western blots revealed a significant knockdown of the p150Glued subunit. The knockdown decreased p150Glued colocalization with microtubules and decreased perinuclear positioning of the convergent microtubular framework. It also inhibited perinuclear aggregation of phagocytosed fluorescent microspheres and reduced mean centripetal microsphere displacement. The findings provide evidence that dynactin p150Glued plays an important role in the functional integrity of the keratinocyte microparasol

Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis

Cellular decision-making is mediated by a complex interplay of external stimuli with the intracellular environment, in particular transcription factor regulatory networks. Here we have determined the expression of a network of 18 key haematopoietic transcription factors in 597 single primary blood stem and progenitor cells isolated from mouse bone marrow. We demonstrate that different stem/progenitor populations are characterized by distinctive transcription factor expression states, and through comprehensive bioinformatic analysis reveal positively and negatively correlated transcription factor pairings, including previously unrecognized relationships between Gata2, Gfi1 and Gfi1b. Validation using transcriptional and transgenic assays confirmed direct regulatory interactions consistent with a regulatory triad in immature blood stem cells, where Gata2 may function to modulate cross-inhibition between Gfi1 and Gfi1b. Single-cell expression profiling therefore identifies network states and allows reconstruction of network hierarchies involved in controlling stem cell fate choices, and provides a blueprint for studying both normal development and human disease

SNAPSHOT USA 2019 : a coordinated national camera trap survey of the United States

This article is protected by copyright. All rights reserved.With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14-week period (17 August - 24 November of 2019). We sampled wildlife at 1509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian's eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the USA. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban-wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot-usa, as well as future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species-specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication.Publisher PDFPeer reviewe

Gene targeting occurs through multiple recombination pathways and is differentially sensitive to chromatin state

Gene targeting is a process in which a double stranded linear DNA fragment is introduced into a genome. This homologous recombination event is dependent on members of the RAD52 epistasis family; however the role that these genes play in targeted gene replacement remains an area of investigation. In this thesis, I describe the development and characterization of a haploid S. cerevisiae system to study the pathways involved in targeted gene replacement. Using this system, I have determined that gene targeting requires POL32 for most events and occurs through alternate RAD51- and RAD59- independent pathways as well as an as yet undetermined RAD51- and RAD59- independent, but RAD52-dependent pathway. Furthermore, I have determined that each of these pathways is mechanistic unique and has different genetic requirements. Finally, I have shown each off these pathways is differentially sensitive to chromatin state as RAD51-independent gene targeting preferentially recombines at sites of heterochromatin, while RAD59 -independent gene targeting occurs more frequently at sites of euchromatin. Taken together, these findings provide insight into the mechanism(s) of gene targeting and may provide a basis for enhancing gene targeting efficiency in other organisms and contexts

Development of in silico models to predict viscosity and mouse clearance using a comprehensive analytical data set collected on 83 scaffold-consistent monoclonal antibodies

ABSTRACTBiologic drug discovery pipelines are designed to deliver protein therapeutics that have exquisite functional potency and selectivity while also manifesting biophysical characteristics suitable for manufacturing, storage, and convenient administration to patients. The ability to use computational methods to predict biophysical properties from protein sequence, potentially in combination with high throughput assays, could decrease timelines and increase the success rates for therapeutic developability engineering by eliminating lengthy and expensive cycles of recombinant protein production and testing. To support development of high-quality predictive models for antibody developability, we designed a sequence-diverse panel of 83 effector functionless IgG1 antibodies displaying a range of biophysical properties, produced and formulated each protein under standard platform conditions, and collected a comprehensive package of analytical data, including in vitro assays and in vivo mouse pharmacokinetics. We used this robust training data set to build machine learning classifier models that can predict complex protein behavior from these data and features derived from predicted and/or experimental structures. Our models predict with 87% accuracy whether viscosity at 150 mg/mL is above or below a threshold of 15 centipoise (cP) and with 75% accuracy whether the area under the plasma drug concentration–time curve (AUC0–672 h) in normal mouse is above or below a threshold of 3.9 × 106 h x ng/mL