Erik F. Y. Hom

Diffusion of Green Fluorescent Protein in the Aqueous-Phase Lumen of Endoplasmic Reticulum

The endoplasmic reticulum (ER) is the major compartment for the processing and quality control of newly synthesized proteins. Green fluorescent protein (GFP) was used as a noninvasive probe to determine the viscous properties of the aqueous lumen of the ER. GFP was targeted to the ER lumen of CHO cells by transient transfection with cDNA encoding GFP (S65T/F64L mutant) with a C-terminus KDEL retention sequence and upstream prolactin secretory sequence. Repeated laser illumination of a fixed 2-micrometers diameter spot resulted in complete bleaching of ER-associated GFP throughout the cell, indicating a continuous ER lumen. A residual amount (<1%) of GFP-KDEL was perinuclear and noncontiguous with the ER, presumably within a pre- or cis-Golgi compartment involved in KDEL-substrate retention. Quantitative spot photobleaching with a single brief bleach pulse indicated that GFP was fully mobile with a t1/2 for fluorescence recovery of 88 +/- 5 ms (SE; 60x lens) and 143 +/- 8 ms (40x). Fluorescence recovery was abolished by paraformaldehyde except for a small component of reversible photobleaching with t1/2 of 3 ms. For comparison, the t1/2 for photobleaching of GFP in cytoplasm was 14 +/- 2 ms (60x) and 24 +/- 1 ms (40x). Utilizing a mathematical model that accounted for ER reticular geometry, a GFP diffusion coefficient of 0.5-1 x 10(-7) cm2/s was computed, 9-18-fold less than that in water and 3-6-fold less than that in cytoplasm. By frequency-domain microfluorimetry, the GFP rotational correlation time was measured to be 39 +/- 8 ns, approximately 2-fold greater than that in water but comparable to that in the cytoplasm. Fluorescence recovery after photobleaching using a 40x lens was measured (at 23 degrees C unless otherwise indicated) for several potential effectors of ER structure and/or lumen environment: t1/2 values (in ms) were 143 +/- 8 (control), 100 +/- 13 (37 degrees C), 53 +/- 13 (brefeldin A), and 139 +/- 6 (dithiothreitol). These results indicate moderately slowed GFP diffusion in a continuous ER lumen.

Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism

Metabolic network reconstruction encompasses existing knowledge about an organisms metabolism and genome annotation, providing a platform for omics data analysis and phenotype prediction. The model alga Chlamydomonas reinhardtii is employed to study diverse biological processes from photosynthesis to phototaxis. Recent heightened interest in this species results from an international movement to develop algal biofuels. Integrating biological and optical data, we reconstructed a genome‐scale metabolic network for this alga and devised a novel light‐modeling approach that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux. We experimentally verified transcripts accounted for in the network and physiologically validated model function through simulation and generation of new experimental growth data, providing high confidence in network contents and predictive applications. The network offers insight into algal metabolism and potential for genetic engineering and efficient light source design, a pioneering resource for studying light‐driven metabolism and quantitative systems biology.

Niche engineering demonstrates a latent capacity for fungal-algal mutualism

It takes two to tango in restricted environments Despite being unrelated, freeliving algae and fungi can learn to help one another out. Hom and Murray raised the green alga Chlamydomonas reinhardtii in CO2-restricted environments in the presence of the yeast Saccharomyces cerevisiae (see the Perspective by Aanen and Bisseling). The experimental setup forced the two species to depend on one another for the metabolic production of CO2, which is provided by the yeast as it consumes glucose and is needed by the alga, and ammonia, which conversely can be made from nitrite by the alga and then used by the yeast. This dependence was seen under a broad range of environmental conditions. Similar tests between other Chlamydomonas and fungal species revealed the ability to create a phylogenetically broad range of mutualisms. Science, this issue p. 94; see also p. 29 Mutualisms between algae and yeast can be created in restrictive environments. [Also see Perspective by Aanen and Bisseling] Mutualistic symbioses shape the evolution of species and ecosystems and catalyze the emergence of biological complexity, yet how such symbioses first form is unclear. We show that an obligate mutualism between the yeast Saccharomyces cerevisiae and the alga Chlamydomonas reinhardtii—two model eukaryotes with very different life histories—can arise spontaneously in an environment requiring reciprocal carbon and nitrogen exchange. This capacity for mutualism is phylogenetically broad, extending to other Chlamydomonas and fungal species. Furthermore, we witnessed the spontaneous association of Chlamydomonas algal cells physically interacting with filamentous fungi. These observations demonstrate that under specific conditions, environmental change induces free-living species to become obligate mutualists and establishes a set of experimentally tractable, phylogenetically related, synthetic systems for studying the evolution of symbiosis.

Metabolic network analysis integrated with transcript verification for sequenced genomes

With sequencing of thousands of organisms completed or in progress, there is a growing need to integrate gene prediction with metabolic network analysis. Using Chlamydomonas reinhardtii as a model, we describe a systems-level methodology bridging metabolic network reconstruction with experimental verification of enzyme encoding open reading frames. Our quantitative and predictive metabolic model and its associated cloned open reading frames provide useful resources for metabolic engineering.

The Chlamydomonas genome project: a decade on

The green alga Chlamydomonas reinhardtii is a popular unicellular organism for studying photosynthesis, cilia biogenesis, and micronutrient homeostasis. Ten years since its genome project was initiated an iterative process of improvements to the genome and gene predictions has propelled this organism to the forefront of the omics era. Housed at Phytozome, the plant genomics portal of the Joint Genome Institute (JGI), the most up-to-date genomic data include a genome arranged on chromosomes and high-quality gene models with alternative splice forms supported by an abundance of whole transcriptome sequencing (RNA-Seq) data. We present here the past, present, and future of Chlamydomonas genomics. Specifically, we detail progress on genome assembly and gene model refinement, discuss resources for gene annotations, functional predictions, and locus ID mapping between versions and, importantly, outline a standardized framework for naming genes.

AIDA: an adaptive image deconvolution algorithm with application to multi-frame and three-dimensional data

We describe an adaptive image deconvolution algorithm (AIDA) for myopic deconvolution of multi-frame and three-dimensional data acquired through astronomical and microscopic imaging. AIDA is a reimplementation and extension of the MISTRAL method developed by Mugnier and co-workers and shown to yield object reconstructions with excellent edge preservation and photometric precision [J. Opt. Soc. Am. A21, 1841 (2004)]. Written in Numerical Python with calls to a robust constrained conjugate gradient method, AIDA has significantly improved run times over the original MISTRAL implementation. Included in AIDA is a scheme to automatically balance maximum-likelihood estimation and object regularization, which significantly decreases the amount of time and effort needed to generate satisfactory reconstructions. We validated AIDA using synthetic data spanning a broad range of signal-to-noise ratios and image types and demonstrated the algorithm to be effective for experimental data from adaptive optics-equipped telescope systems and wide-field microscopy.

A Unified Taxonomy for Ciliary Dyneins

The formation and function of eukaryotic cilia/flagella require the action of a large array of dynein microtubule motor complexes. Due to genetic, biochemical, and microscopic tractability, Chlamydomonas reinhardtii has become the premier model system in which to dissect the role of dyneins in flagellar assembly, motility, and signaling. Currently, 54 proteins have been described as components of various Chlamydomonas flagellar dyneins or as factors required for their assembly in the cytoplasm and/or transport into the flagellum; orthologs of nearly all these components are present in other ciliated organisms including humans. For historical reasons, the nomenclature of these diverse dynein components and their corresponding genes, mutant alleles, and orthologs has become extraordinarily confusing. Here, we unify Chlamydomonas dynein gene nomenclature and establish a systematic classification scheme based on structural properties of the encoded proteins. Furthermore, we provide detailed tabulations of the various mutant alleles and protein aliases that have been used and explicitly define the correspondence with orthologous components in other model organisms and humans.

WD60/FAP163 is a dynein intermediate chain required for retrograde intraflagellar transport in cilia

WD60/FAP163 is identified as an additional intermediate chain of the dynein that powers retrograde intraflagellar transport. Lack of WD60/FAP163 results in a severe ciliary assembly defect.

Whole-Genome Resequencing Reveals Extensive Natural Variation in the Model Green Alga Chlamydomonas reinhardtii.

Whole-genome resequencing of Chlamydomonas reveals enormous intraspecific diversity and a reservoir of naturally occurring variation, including candidate loss-of-function alleles. We performed whole-genome resequencing of 12 field isolates and eight commonly studied laboratory strains of the model organism Chlamydomonas reinhardtii to characterize genomic diversity and provide a resource for studies of natural variation. Our data support previous observations that Chlamydomonas is among the most diverse eukaryotic species. Nucleotide diversity is ∼3% and is geographically structured in North America with some evidence of admixture among sampling locales. Examination of predicted loss-of-function mutations in field isolates indicates conservation of genes associated with core cellular functions, while genes in large gene families and poorly characterized genes show a greater incidence of major effect mutations. De novo assembly of unmapped reads recovered genes in the field isolates that are absent from the CC-503 assembly. The laboratory reference strains show a genomic pattern of polymorphism consistent with their origin as the recombinant progeny of a diploid zygospore. Large duplications or amplifications are a prominent feature of laboratory strains and appear to have originated under laboratory culture. Extensive natural variation offers a new source of genetic diversity for studies of Chlamydomonas, including naturally occurring alleles that may prove useful in studies of gene function and the dissection of quantitative genetic traits.

Analysis of Coupled Bimolecular Reaction Kinetics and Diffusion by Two-Color Fluorescence Correlation Spectroscopy: Enhanced Resolution of Kinetics by Resonance Energy Transfer

In two-color fluorescence correlation spectroscopy (TCFCS), the fluorescence intensities of two fluorescently-labeled species are cross-correlated over time and can be used to identify static and dynamic interactions. Generally, fluorophore labels are chosen that do not undergo Förster resonance energy transfer (FRET). Here, a general TCFCS theory is presented that accounts for the possibility of FRET between reactants in the reversible bimolecular reaction, [reaction: see text] where k(f) and k(b) are forward and reverse rate constants, respectively (dissociation constant K(d) = k(b)/k(f)). Using this theory, we systematically investigated the influence on the correlation function of FRET, reaction rates, reactant concentrations, diffusion, and component visibility. For reactants of comparable size and an energy-transfer efficiency of approximately 90%, experimentally measurable cross-correlation functions should be sensitive to reaction kinetics for K(d) > 10(-8) M and k(f) >or= approximately 10(7) M(-1)s(-1). Measured auto-correlation functions corresponding to donor and acceptor labels are generally less sensitive to reaction kinetics, although for the acceptor, this sensitivity increases as the visibility of the donor increases relative to the acceptor. In the absence of FRET or a significant hydrodynamic difference between reactant species, there is little effect of reaction kinetics on the shape of auto- and cross-correlation functions. Our results suggest that a subset of biologically relevant association-dissociation kinetics can be measured by TCFCS and that FRET can be advantageous in enhancing these effects.