SHR and SCR coordinate root patterning and growth early in the cell cycle.

Precise control of cell division is essential for proper patterning and growth during the development of multicellular organisms. Coordination of formative divisions that generate new tissue patterns with proliferative divisions that promote growth is poorly understood. SHORTROOT (SHR) and SCARECROW (SCR) are transcription factors that are required for formative divisions in the stem cell niche of Arabidopsis roots1,2. Here we show that levels of SHR and SCR early in the cell cycle determine the orientation of the division plane, resulting in either formative or proliferative cell division. We used 4D quantitative, long-term and frequent (every 15 min for up to 48 h) light sheet and confocal microscopy to probe the dynamics of SHR and SCR in tandem within single cells of living roots. Directly controlling their dynamics with an SHR induction system enabled us to challenge an existing bistable model3 of the SHR-SCR gene-regulatory network and to identify key features that are essential for rescue of formative divisions in shr mutants. SHR and SCR kinetics do not align with the expected behaviour of a bistable system, and only low transient levels, present early in the cell cycle, are required for formative divisions. These results reveal an uncharacterized mechanism by which developmental regulators directly coordinate patterning and growth.

Development of Transient Recombinant Expression and Affinity Chromatography Systems for Human Fibrinogen.

Fibrin forms the structural scaffold of blood clots and has great potential for biomaterial applications. Creating recombinant expression systems of fibrinogen, fibrin's soluble precursor, would advance the ability to construct mutational libraries that would enable structure-function studies of fibrinogen and expand the utility of fibrin as a biomaterial. Despite these needs, recombinant fibrinogen expression systems, thus far, have relied on the time-consuming creation of stable cell lines. Here we present tests of a transient fibrinogen expression system that can rapidly generate yields of 8-12 mg/L using suspension HEK Expi293TM cells. We report results from two different plasmid systems encoding the fibrinogen cDNAs and two different transfection reagents. In addition, we describe a novel, affinity-based approach to purifying fibrinogen from complex media such as human plasma. We show that using a high-affinity peptide which mimics fibrin's knob 'A' sequence enables the purification of 50-75% of fibrinogen present in plasma. Having robust expression and purification systems of fibrinogen will enable future studies of basic fibrin(ogen) biology, while paving the way for the ubiquitous use of fibrin as a biomaterial.

High-resolution metabolic mapping of cell types in plant roots.

Metabolite composition offers a powerful tool for understanding gene function and regulatory processes. However, metabolomics studies on multicellular organisms have thus far been performed primarily on whole organisms, organs, or cell lines, losing information about individual cell types within a tissue. With the goal of profiling metabolite content in different cell populations within an organ, we used FACS to dissect GFP-marked cells from Arabidopsis roots for metabolomics analysis. Here, we present the metabolic profiles obtained from five GFP-tagged lines representing core cell types in the root. Fifty metabolites were putatively identified, with the most prominent groups being glucosinolates, phenylpropanoids, and dipeptides, the latter of which is not yet explored in roots. The mRNA expression of enzymes or regulators in the corresponding biosynthetic pathways was compared with the relative metabolite abundance. Positive correlations suggest that the rate-limiting steps in biosynthesis of glucosinolates in the root are oxidative modifications of side chains. The current study presents a work flow for metabolomics analyses of cell-type populations.

Comprehensive Analysis of the Role of Fibrinogen and Thrombin in Clot Formation and Structure for Plasma and Purified Fibrinogen.

Altered properties of fibrin clots have been associated with bleeding and thrombotic disorders, including hemophilia or trauma and heart attack or stroke. Clotting factors, such as thrombin and tissue factor, or blood plasma proteins, such as fibrinogen, play critical roles in fibrin network polymerization. The concentrations and combinations of these proteins affect the structure and stability of clots, which can lead to downstream complications. The present work includes clots made from plasma and purified fibrinogen and shows how varying fibrinogen and activation factor concentrations affect the fibrin properties under both conditions. We used a combination of scanning electron microscopy, confocal microscopy, and turbidimetry to analyze clot/fiber structure and polymerization. We quantified the structural and polymerization features and found similar trends with increasing/decreasing fibrinogen and thrombin concentrations for both purified fibrinogen and plasma clots. Using our compiled results, we were able to generate multiple linear regressions that predict structural and polymerization features using various fibrinogen and clotting agent concentrations. This study provides an analysis of structural and polymerization features of clots made with purified fibrinogen or plasma at various fibrinogen and clotting agent concentrations. Our results could be utilized to aid in interpreting results, designing future experiments, or developing relevant mathematical models.

"Modeling Diffusive Search by Non-Adaptive Sperm: Empirical and Computational Insights".

During fertilization, mammalian sperm undergo a winnowing selection process that reduces the candidate pool of potential fertilizers from ~106-1011 cells to 101-102 cells (depending on the species). Classical sperm competition theory addresses the positive or 'stabilizing' selection that acts on sperm phenotypes within populations of organisms but does not strictly address the developmental consequences of sperm traits among individual organisms that are under purifying selection during fertilization. It is the latter that is of utmost concern for improving assisted reproductive technologies (ART) because 'low fitness' sperm may be inadvertently used for fertilization during interventions that rely heavily on artificial sperm selection, such as intracytoplasmic sperm injection (ICSI). Importantly, some form of sperm selection is used in nearly all forms of ART (e.g., differential centrifugation, swim-up, or hyaluronan binding assays, etc.). To date, there is no unifying quantitative framework (i.e., theory of sperm selection) that synthesizes causal mechanisms of selection with observed natural variation in individual sperm traits. In this report, we reframe the physiological function of sperm as a collective diffusive search process and develop multi-scale computational models to explore the causal dynamics that constrain sperm 'fitness' during fertilization. Several experimentally useful concepts are developed, including a probabilistic measure of sperm 'fitness' as well as an information theoretic measure of the magnitude of sperm selection, each of which are assessed under systematic increases in microenvironmental selective pressure acting on sperm motility patterns.

What is the diameter of a fibrin fiber?

Background: Altered fibrin fiber structure is linked to pathologic states, including coronary heart disease, ischemic stroke, and atherosclerosis. However, several different techniques are commonly utilized for studying fibrin structures, and comparison of results obtained using different techniques can be challenging due to lack of standardization. Objectives: This study provides a path toward standardization by comparing fibrin fiber diameters for a range of physiologic fibrinogen and thrombin concentrations using multiple different complementary experimental methods. Methods: We determined fiber diameter using scanning electron microscopy (SEM), superresolution (stochastic optical reconstruction microscopy) fluorescence microscopy, and 4 commonly utilized turbidimetric approaches to determine the congruence between the results and the conditions under which each should be used. Results: We found that diameter values obtained using SEM and superresolution imaging agree within 10% for nearly all conditions tested. We also found that when a wavelength range of 500 to 800 nm was used for measurements and accounting for the wavelength dependence of the refractive index and specific refractive index increment, diameters obtained using the corrected Yeromonahos turbidimetric approach agree with SEM within 20% for most conditions. Conclusion: We performed a systematic, multitechnique survey assessing fibrin fiber diameters under a range of biochemical conditions. The similarity in the diameter values obtained using SEM and superresolution imaging suggests that drying and fixation during SEM sample preparation do not dramatically alter fiber cross-sections. Congruence, under certain conditions, between diameter values obtained using SEM, superresolution fluorescence imaging, and turbidimetry demonstrates the feasibility of a fibrin diameter standardization project.

The Applicability of Current Turbidimetric Approaches for Analyzing Fibrin Fibers and Other Filamentous Networks.

Turbidimetry is an experimental technique often used to study the structure of filamentous networks. To extract structural properties such as filament diameter from turbidimetric data, simplifications to light scattering theory must be employed. In this work, we evaluate the applicability of three commonly utilized turbidimetric analysis approaches, each using slightly different simplifications. We make a specific application towards analyzing fibrin fibers, which form the structural scaffold of blood clots, but the results are generalizable. Numerical simulations were utilized to assess the applicability of each approach across a range of fiber lengths and diameters. Simulation results indicated that all three turbidimetric approaches commonly underestimate fiber diameter, and that the "Carr-Hermans" approach, utilizing wavelengths in the range of 500−800 nm, provided <10% error for the largest number of diameter/length combinations. These theoretical results were confirmed, under select conditions, via the comparison of fiber diameters extracted from experimental turbidimetric data, with diameters obtained using super-resolution microscopy.

Imaging and analysis platform for automatic phenotyping and trait ranking of plant root systems.

The ability to nondestructively image and automatically phenotype complex root systems, like those of rice (Oryza sativa), is fundamental to identifying genes underlying root system architecture (RSA). Although root systems are central to plant fitness, identifying genes responsible for RSA remains an underexplored opportunity for crop improvement. Here we describe a nondestructive imaging and analysis system for automated phenotyping and trait ranking of RSA. Using this system, we image rice roots from 12 genotypes. We automatically estimate RSA traits previously identified as important to plant function. In addition, we expand the suite of features examined for RSA to include traits that more comprehensively describe monocot RSA but that are difficult to measure with traditional methods. Using 16 automatically acquired phenotypic traits for 2,297 images from 118 individuals, we observe (1) wide variation in phenotypes among the genotypes surveyed; and (2) greater intergenotype variance of RSA features than variance within a genotype. RSA trait values are integrated into a computational pipeline that utilizes supervised learning methods to determine which traits best separate two genotypes, and then ranks the traits according to their contribution to each pairwise comparison. This trait-ranking step identifies candidate traits for subsequent quantitative trait loci analysis and demonstrates that depth and average radius are key contributors to differences in rice RSA within our set of genotypes. Our results suggest a strong genetic component underlying rice RSA. This work enables the automatic phenotyping of RSA of individuals within mapping populations, providing an integrative framework for quantitative trait loci analysis of RSA.