2019 Social Impact Annual Report: Chocolate Milk: The Documentary

Chocolate Milk is a graybayne film/media production, directed and produced by Elizabeth Gray Bayne. The project began in 2014 as a digital storytelling project in which the personal breastfeeding stories of African American mothers were collected and hosted on a YouTube channel called Chocolate Milk: The Documentary Series. Over the course of three seasons, the series became a tool for health centers and physicians' offices across the United States. After working closely with community stakeholders to better understand the racial breastfeeding disparities affecting black mothers in the U.S., the team set about producing Chocolate Milk: The Documentary, a 90-minute film with a primary target audience of African American women ages 18 through 34 and a secondary audience of family members, health providers and the general public. An early cut of the film, which follows three African American women, a new mother, a homebirth midwife and WIC lactation expert, was previewed in 200 communities nationwide during National Breastfeeding Month and Black Breastfeeding Week in August 2019.These community screenings demonstrated the effectiveness of Chocolate Milk: The Documentary in increasing community support for black breastfeeding mothers by galvanizing organizations, the public, and policymakers. In this report, the results of an audience survey and the overall findings from the national social impact campaign for the film will be presented, demonstrating the value of narrative in raising awareness and community support for breastfeeding

Systems-level discovery of quality attributes and candidate pathways for optimized production of human pluripotent stem cell-derived cardiomyocytes

Numerous protocols exist for differentiation of human pluripotent stem cells (hPSCs) to cardiomyocytes (CMs). Although these methods have improved in efficiency over the past decade, they remain highly variable in their resultant purities, not only among different source hPSC lines but also between batches in the same cell line. This substantial heterogeneity of hPSC-CM product outcomes points to poorly-understood, highly sensitive, and uncontrolled variables present within the overall process. Herein, we have undertaken a multi-omic discovery approach to identify key temporal differences in cell attributes between high- and low-purity hPSC-CM differentiations to provide systems-level insights into underlying mechanisms which drive these populations to divergent endpoints. Specifically, we are combining metabolomic, proteomic, lipidomic, and transcriptomic analyses collected throughout the differentiation process for high- and low-purity (as assessed by %cTnT+ via flow cytometry) differentiation batches. In addition to gaining fundamental insights into the underlying biology of the differentiation process, we are extending our analyses to 1) identify putative critical quality attributes for use in on- or at-line analytics for continuous process monitoring, 2) enhance process robustness through the development of protocols aimed at depressing off-target pathways and enhancing on-target ones, and 3) establish potential feedforward/feedback control schemes based on real-time analytics to respond to in-process intermediate quality attributes through rational adjustment of process parameters. To date we have identified novel putative candidate quality attributes for process monitoring and cellular pathways which may be able to be modulated to augment process robustness in a scaled manufacturing context. Beyond standard single-omic analytical workflows, ongoing work is aimed at integrating these data for deepened insight, including functional integration with systems-scale modeling and high-dimensional machine-learning methodologies to extract dynamic relationships among variables over time

Global regulation of heterochromatin spreading by Leo1

Heterochromatin plays important roles in eukaryotic genome regulation. However, the repressive nature of heterochromatin combined with its propensity to self-propagate necessitates robust mechanisms to contain heterochromatin within defined boundaries and thus prevent silencing of expressed genes. Here we show that loss of the PAF complex (PAFc) component Leo1 compromises chromatin boundaries, resulting in invasion of heterochromatin into flanking euchromatin domains. Similar effects are seen upon deletion of other PAFc components, but not other factors with related functions in transcription-associated chromatin modification, indicating a specific role for PAFc in heterochromatin regulation. Loss of Leo1 results in reduced levels of H4K16 acetylation at boundary regions, while tethering of the H4K16 acetyltransferase Mst1 to boundary chromatin suppresses heterochromatin spreading in leo1 Delta cells, suggesting that Leo1 antagonises heterochromatin spreading by promoting H4K16 acetylation. Our findings reveal a previously undescribed role for PAFc in regulating global heterochromatin distribution

Split-Brain: what we know now and why this is important for understanding consciousness

Recently, the discussion regarding the consequences of cutting the corpus callosum (“split-brain”) has regained momentum (Corballis, Corballis, Berlucchi, & Marzi, 2018; Pinto et al., 2017; Pinto, Lamme, & de Haan, 2017; Volz & Gazzaniga, 2017; Volz, Hillyard, Miller, & Gazzaniga, 2018). This collective review paper aims to summarize the empirical common ground, to delineate the different interpretations, and to identify the remaining questions. In short, callosotomy leads to a broad breakdown of functional integration ranging from perception to attention. However, the breakdown is not absolute as several processes, such as action control, seem to remain unified. Disagreement exists about the responsible mechanisms for this remaining unity. The main issue concerns the first-person perspective of a split-brain patient. Does a split-brain harbor a split consciousness or is consciousness unified? The current consensus is that the body of evidence is insufficient to answer this question, and different suggestions are made to how future studies might address this paucity. In addition, it is suggested that the answers might not be a simple yes or no but that intermediate conceptualization need to be considered

A systematic genetic screen identifies new factors influencing centromeric heterochromatin integrity in fission yeast

BACKGROUND: Heterochromatin plays important roles in the regulation and stability of eukaryotic genomes. Both heterochromatin components and pathways that promote heterochromatin assembly, including RNA interference, RNAi, are broadly conserved between the fission yeast Schizosaccharomyces pombe and humans. As a result, fission yeast has emerged as an important model system for dissecting mechanisms governing heterochromatin integrity. Thus far, over 50 proteins have been found to contribute to heterochromatin assembly at fission yeast centromeres. However, previous studies have not been exhaustive, and it is therefore likely that further factors remain to be identified. RESULTS: To gain a more complete understanding of heterochromatin assembly pathways, we have performed a systematic genetic screen for factors required for centromeric heterochromatin integrity. In addition to known RNAi and chromatin modification components, we identified several proteins with previously undescribed roles in heterochromatin regulation. These included both known and newly characterised splicing-associated proteins, which are required for proper processing of centromeric transcripts by the RNAi pathway, and COP9 signalosome components Csn1 and Csn2, whose role in heterochromatin assembly can be explained at least in part by a role in the Ddb1-dependent degradation of the heterochromatin regulator Epe1. CONCLUSIONS: This work has revealed new factors involved in RNAi-directed heterochromatin assembly in fission yeast. Our findings support and extend previous observations that implicate components of the splicing machinery as a platform for RNAi, and demonstrate a novel role for the COP9 signalosome in heterochromatin regulation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-014-0481-4) contains supplementary material, which is available to authorized users

Analysis of small RNA in fission yeast; centromeric siRNAs are potentially generated through a structured RNA

The formation of heterochromatin at the centromeres in fission yeast depends on transcription of the outer repeats. These transcripts are processed into siRNAs that target homologous loci for heterochromatin formation. Here, high throughput sequencing of small RNA provides a comprehensive analysis of centromere-derived small RNAs. We found that the centromeric small RNAs are Dcr1 dependent, carry 5′-monophosphates and are associated with Ago1. The majority of centromeric small RNAs originate from two remarkably well-conserved sequences that are present in all centromeres. The high degree of similarity suggests that this non-coding sequence in itself may be of importance. Consistent with this, secondary structure-probing experiments indicate that this centromeric RNA is partially double-stranded and is processed by Dicer in vitro. We further demonstrate the existence of small centromeric RNA in rdp1Δ cells. Our data suggest a pathway for siRNA generation that is distinct from the well-documented model involving RITS/RDRC. We propose that primary transcripts fold into hairpin-like structures that may be processed by Dcr1 into siRNAs, and that these siRNAs may initiate heterochromatin formation independent of RDRC activity

MASH Explorer: A Universal Software Environment for Top-Down Proteomics

Top-down mass spectrometry (MS)-based proteomics enable a comprehensive analysis of proteoforms with molecular specificity to achieve a proteome-wide understanding of protein functions. However, the lack of a universal software for top-down proteomics is becoming increasingly recognized as a major barrier, especially for newcomers. Here, we have developed MASH Explorer, a universal, comprehensive, and user-friendly software environment for top-down proteomics. MASH Explorer integrates multiple spectral deconvolution and database search algorithms into a single, universal platform which can process top-down proteomics data from various vendor formats, for the first time. It addresses the urgent need in the rapidly growing top-down proteomics community and is freely available to all users worldwide. With the critical need and tremendous support from the community, we envision that this MASH Explorer software package will play an integral role in advancing top-down proteomics to realize its full potential for biomedical research

Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species–season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds