Gaussian mixture models and machine learning predict megakaryocytic growth and differentiation potential ex vivo

The ability to analyze single cells via flow cytometry has resulted in a wide range of biological and medical applications. Currently, there is no established framework to compare and interpret time-series flow cytometry data for cell engineering applications. Manual analysis of temporal trends is time-consuming and subjective for large-scale datasets. We resolved this bottleneck by developing TEmporal Gaussian Mixture models (TEGM), an unbiased computational strategy to quantify and predict temporal trends of developing cell subpopulations indicative of cellular phenotype. TEGM applies Gaussian mixture models and gradient boosted trees for cell engineering applications. TEGM enables the extraction of subtle features, such as the dispersion and rate of change of surface marker expression for each subpopulation over time. These critical, yet hard-to-discern, features are fed into machine-learning algorithms that predict underlying cell classes. Our framework can be flexibly applied to conventional flow cytometry sampling schemes, and allows for faster and more consistent processing of time-series flow cytometry data. Please click Additional Files below to see the full abstract

Using Gaussian mixture models and machine learning to predict donor- dependent megakaryocytic cell growth and differentiation potential ex vivo

The ability to analyze single cells via flow cytometry has resulted in a wide range of biological and medical applications. Currently, there is no established framework to compare and interpret time-series flow cytometry data for cell engineering applications. Manual analysis of temporal trends is time-consuming and subjective for large-scale datasets. We resolved this bottleneck by developing TEmporal Gaussian Mixture models (TEGM), an unbiased computational strategy to quantify and predict temporal trends of developing cell subpopulations indicative of cellular phenotype.. Please click Additional Files below to see the full abstract

Identification of novel enzymes to enhance the ruminal digestion of barley straw

Crude enzyme extracts typically contain a broad spectrum of enzyme activities, most of which are redundant to those naturally produced by the rumen microbiome. Identification of enzyme activities that are synergistic to those produced by the rumen microbiome could enable formulation of enzyme cocktails that improve fiber digestion in ruminants. Compared to untreated barley straw, Viscozyme® increased gas production, dry matter digestion (P<0.01) and volatile fatty acid production (P<0.001) in ruminal batch cultures. Fractionation of Viscozyme® by Blue Native PAGE and analyses using a microassay and mass-spectrometry revealed a GH74 endoglucanase, GH71 α-1,3-glucanase, GH5 mannanase, GH7 cellobiohydrolase, GH28 pectinase, and esterases from Viscozyme® contributed to enhanced saccharification of barley straw by rumen mix enzymes. Grouping of these identified activities with their carbohydrate active enzymes (CAZy) counterparts enabled selection of similar CAZymes for downstream production and screening. Mining of these specific activities from other biological systems could lead to high value enzyme formulations for ruminants

Discovery and characterization of family 39 glycoside hydrolases from rumen anaerobic fungi with polyspecific activity on rare arabinosyl substrates

Enzyme activities that improve digestion of recalcitrant plant cell wall polysaccharides may offer solutions for sustainable industries. To this end, anaerobic fungi in the rumen have been identified as a promising source of novel carbohydrate active enzymes (CAZymes) that modify plant cell wall polysaccharides and other complex glycans. Many CAZymes share insufficient sequence identity to characterized proteins from other microbial ecosystems to infer their function; thus presenting challenges to their identification. In this study, four rumen fungal genes (nf2152, nf2215, nf2523, and pr2455) were identified that encode family 39 glycoside hydrolases (GH39s), and have conserved structural features with GH51s. Two recombinant proteins, NF2152 and NF2523, were characterized using a variety of biochemical and structural techniques, and were determined to have distinct catalytic activities. NF2152 releases a single product, β1,2-arabinobiose (Ara2) from sugar beet arabinan (SBA), and β1,2-Ara2 and α-1,2-galactoarabinose (Gal-Ara) from rye arabinoxylan (RAX). NF2523 exclusively releases α-1,2-Gal-Ara from RAX, which represents the first description of a galacto-(α-1,2)-arabinosidase. Both β-1,2-Ara2 and α-1,2-Gal-Ara are disaccharides not previously described within SBA and RAX. In this regard, the enzymes studied here may represent valuable new biocatalytic tools for investigating the structures of rare arabinosyl-containing glycans, and potentially for facilitating their modification in industrial applications

Scenario Planning and Nanotechnological Futures

Scenario planning may assist us in harnessing the benefits of nanotechnology and managing the associated risks for the good of the society. Scenario planning is a way to describe the present state of the world and develop several hypotheses about the future of the world, thereby enabling discussions about how the world ought to be. Scenario planning thus is not only a tool for learning and foresight, but also for leadership. Informed decision-making by experts and political leaders becomes possible, while simultaneously allaying public's perception of the risks of new and emerging technologies such as nanotechnology. Two scenarios of the societal impact of nanotechnology are the mixed-signals scenario and the confluence scenario. Technoscientists have major roles to play in both scenarios

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Combinatorial Glycomic Analyses to Direct CAZyme Discovery for the Tailored Degradation of Canola Meal Non-Starch Dietary Polysaccharides

Canola meal (CM), the protein-rich by-product of canola oil extraction, has shown promise as an alternative feedstuff and protein supplement in poultry diets, yet its use has been limited due to the abundance of plant cell wall fibre, specifically non-starch polysaccharides (NSP) and lignin. The addition of exogenous enzymes to promote the digestion of CM NSP in chickens has potential to increase the metabolizable energy of CM. We isolated chicken cecal bacteria from a continuous-flow mini-bioreactor system and selected for those with the ability to metabolize CM NSP. Of 100 isolates identified, Bacteroides spp. and Enterococcus spp. were the most common species with these capabilities. To identify enzymes specifically for the digestion of CM NSP, we used a combination of glycomics techniques, including enzyme-linked immunosorbent assay characterization of the plant cell wall fractions, glycosidic linkage analysis (methylation-GC-MS analysis) of CM NSP and their fractions, bacterial growth profiles using minimal media supplemented with CM NSP, and the sequencing and de novo annotation of bacterial genomes of high-efficiency CM NSP utilizing bacteria. The SACCHARIS pipeline was used to select plant cell wall active enzymes for recombinant production and characterization. This approach represents a multidisciplinary innovation platform to bioprospect endogenous CAZymes from the intestinal microbiota of herbivorous and omnivorous animals which is adaptable to a variety of applications and dietary polysaccharides