Systematic identification and characterization of genes in the regulation and biogenesis of photosynthetic machinery.

Photosynthesis is central to food production and the Earth's biogeochemistry, yet the molecular basis for its regulation remains poorly understood. Here, using high-throughput genetics in the model eukaryotic alga Chlamydomonas reinhardtii, we identify with high confidence (false discovery rate [FDR] < 0.11) 70 poorly characterized genes required for photosynthesis. We then enable the functional characterization of these genes by providing a resource of proteomes of mutant strains, each lacking one of these genes. The data allow assignment of 34 genes to the biogenesis or regulation of one or more specific photosynthetic complexes. Further analysis uncovers biogenesis/regulatory roles for at least seven proteins, including five photosystem I mRNA maturation factors, the chloroplast translation factor MTF1, and the master regulator PMR1, which regulates chloroplast genes via nuclear-expressed factors. Our work provides a rich resource identifying regulatory and functional genes and placing them into pathways, thereby opening the door to a system-level understanding of photosynthesis.

The emergence of proteome-wide technologies: systematic analysis of proteins comes of age.

During the lifetime of a cell proteins can change their localization, alter their abundance and undergo modifications, all of which cannot be assayed by tracking mRNAs alone. Methods to study proteomes directly are coming of age, thereby opening new perspectives on the role of post-translational regulation in stabilizing the cellular milieu. Proteomics has undergone a revolution, and novel technologies for the systematic analysis of proteins have emerged. These methods can expand our ability to acquire information from single proteins to proteomes, from static to dynamic measures and from the population level to the level of single cells. Such approaches promise that proteomes will soon be studied at a similar level of dynamic resolution as has been the norm for transcriptomes.

Fate mapping reveals origins and dynamics of monocytes and tissue macrophages under homeostasis.

Mononuclear phagocytes, including monocytes, macrophages, and dendritic cells, contribute to tissue integrity as well as to innate and adaptive immune defense. Emerging evidence for labor division indicates that manipulation of these cells could bear therapeutic potential. However, specific ontogenies of individual populations and the overall functional organization of this cellular network are not well defined. Here we report a fate-mapping study of the murine monocyte and macrophage compartment taking advantage of constitutive and conditional CX(3)CR1 promoter-driven Cre recombinase expression. We have demonstrated that major tissue-resident macrophage populations, including liver Kupffer cells and lung alveolar, splenic, and peritoneal macrophages, are established prior to birth and maintain themselves subsequently during adulthood independent of replenishment by blood monocytes. Furthermore, we have established that short-lived Ly6C(+) monocytes constitute obligatory steady-state precursors of blood-resident Ly6C(-) cells and that the abundance of Ly6C(+) blood monocytes dynamically controls the circulation lifespan of their progeny.

The yeast ER-intramembrane protease Ypf1 refines nutrient sensing by regulating transporter abundance.

Proteolysis by aspartyl intramembrane proteases such as presenilin and signal peptide peptidase (SPP) underlies many cellular processes in health and disease. Saccharomyces cerevisiae encodes a homolog that we named yeast presenilin fold 1 (Ypf1), which we verify to be an SPP-type protease that localizes to the endoplasmic reticulum (ER). Our work shows that Ypf1 functionally interacts with the ER-associated degradation (ERAD) factors Dfm1 and Doa10 to regulate the abundance of nutrient transporters by degradation. We demonstrate how this noncanonical branch of the ERAD pathway, which we termed "ERAD regulatory" (ERAD-R), responds to ligand-mediated sensing as a trigger. More generally, we show that Ypf1-mediated posttranslational regulation of plasma membrane transporters is indispensible for early sensing and adaptation to nutrient depletion. The combination of systematic analysis alongside mechanistic details uncovers a broad role of intramembrane proteolysis in regulating secretome dynamics.

AMPK regulates ESCRT-dependent microautophagy of proteasomes concomitant with proteasome storage granule assembly during glucose starvation.

The ubiquitin-proteasome system regulates numerous cellular processes and is central to protein homeostasis. In proliferating yeast and many mammalian cells, proteasomes are highly enriched in the nucleus. In carbon-starved yeast, proteasomes migrate to the cytoplasm and collect in proteasome storage granules (PSGs). PSGs dissolve and proteasomes return to the nucleus within minutes of glucose refeeding. The mechanisms by which cells regulate proteasome homeostasis under these conditions remain largely unknown. Here we show that AMP-activated protein kinase (AMPK) together with endosomal sorting complexes required for transport (ESCRTs) drive a glucose starvation-dependent microautophagy pathway that preferentially sorts aberrant proteasomes into the vacuole, thereby biasing accumulation of functional proteasomes in PSGs. The proteasome core particle (CP) and regulatory particle (RP) are regulated differently. Without AMPK, the insoluble protein deposit (IPOD) serves as an alternative site that specifically sequesters CP aggregates. Our findings reveal a novel AMPK-controlled ESCRT-mediated microautophagy mechanism in the regulation of proteasome trafficking and homeostasis under carbon starvation.

Comprehensive Discovery of Cell-Cycle-Essential Pathways in Chlamydomonas reinhardtii.

We generated a large collection of temperature-sensitive lethal mutants in the unicellular green alga Chlamydomonas reinhardtii, focusing on mutations specifically affecting cell cycle regulation. We used UV mutagenesis and robotically assisted phenotypic screening to isolate candidates. To overcome the bottleneck at the critical step of molecular identification of the causative mutation ("driver"), we developed MAPS-SEQ (meiosis-assisted purifying selection sequencing), a multiplexed genetic/bioinformatics strategy. MAPS-SEQ allowed us to perform multiplexed simultaneous determination of the driver mutations from hundreds of neutral "passenger" mutations in each member of a large pool of mutants. This method should work broadly, including in multicellular diploid genetic systems, for any scorable trait. Using MAPS-SEQ, we identified essential genes spanning a wide range of molecular functions. Phenotypic clustering based on DNA content analysis and cell morphology indicated that the mutated genes function in the cell cycle at multiple points and by diverse mechanisms. The collection is sufficiently complete to allow specific conditional inactivation of almost all cell-cycle-regulatory pathways. Approximately seventy-five percent of the essential genes identified in this project had clear orthologs in land plant genomes, a huge enrichment compared with the value of ∼20% for the Chlamydomonas genome overall. Findings about these mutants will likely have direct relevance to essential cell biology in land plants.

Iron affects Ire1 clustering propensity and the amplitude of endoplasmic reticulum stress signaling.

The unfolded protein response (UPR) allows cells to adjust secretory pathway capacity according to need. Ire1, the endoplasmic reticulum (ER) stress sensor and central activator of the UPR is conserved from the budding yeast Saccharomyces cerevisiae to humans. Under ER stress conditions, Ire1 clusters into foci that enable optimal UPR activation. To discover factors that affect Ire1 clustering, we performed a high-content screen using a whole-genome yeast mutant library expressing Ire1-mCherry. We imaged the strains following UPR induction and found 154 strains that displayed alterations in Ire1 clustering. The hits were enriched for iron and heme effectors and binding proteins. By performing pharmacological depletion and repletion, we confirmed that iron (Fe3+) affects UPR activation in both yeast and human cells. We suggest that Ire1 clustering propensity depends on membrane composition, which is governed by heme-dependent biosynthesis of sterols. Our findings highlight the diverse cellular functions that feed into the UPR and emphasize the cross-talk between organelles required to concertedly maintain homeostasis.

Heterosis as a consequence of regulatory incompatibility.

BACKGROUND: The merging of genomes in inter-specific hybrids can result in novel phenotypes, including increased growth rate and biomass yield, a phenomenon known as heterosis. Heterosis is typically viewed as the opposite of hybrid incompatibility. In this view, the superior performance of the hybrid is attributed to heterozygote combinations that compensate for deleterious mutations accumulating in each individual genome, or lead to new, over-dominating interactions with improved performance. Still, only fragmented knowledge is available on genes and processes contributing to heterosis. RESULTS: We describe a budding yeast hybrid that grows faster than both its parents under different environments. Phenotypically, the hybrid progresses more rapidly through cell cycle checkpoints, relieves the repression of respiration in fast growing conditions, does not slow down its growth when presented with ethanol stress, and shows increased signs of DNA damage. A systematic genetic screen identified hundreds of S. cerevisiae alleles whose deletion reduced growth of the hybrid. These growth-affecting alleles were condition-dependent, and differed greatly from alleles that reduced the growth of the S. cerevisiae parent. CONCLUSIONS: Our results define a budding yeast hybrid that is perturbed in multiple regulatory processes but still shows a clear growth heterosis. We propose that heterosis results from incompatibilities that perturb regulatory mechanisms, which evolved to protect cells against damage or prepare them for future challenges by limiting cell growth.

LoQAtE--Localization and Quantitation ATlas of the yeast proteomE. A new tool for multiparametric dissection of single-protein behavior in response to biological perturbations in yeast.

Living organisms change their proteome dramatically to sustain a stable internal milieu in fluctuating environments. To study the dynamics of proteins during stress, we measured the localization and abundance of the Saccharomyces cerevisiae proteome under various growth conditions and genetic backgrounds using the GFP collection. We created a database (DB) called 'LoQAtE' (Localizaiton and Quantitation Atlas of the yeast proteomE), available online at http://www.weizmann.ac.il/molgen/loqate/, to provide easy access to these data. Using LoQAtE DB, users can get a profile of changes for proteins of interest as well as querying advanced intersections by either abundance changes, primary localization or localization shifts over the tested conditions. Currently, the DB hosts information on 5330 yeast proteins under three external perturbations (DTT, H2O2 and nitrogen starvation) and two genetic mutations [in the chaperonin containing TCP1 (CCT) complex and in the proteasome]. Additional conditions will be uploaded regularly. The data demonstrate hundreds of localization and abundance changes, many of which were not detected at the level of mRNA. LoQAtE is designed to allow easy navigation for non-experts in high-content microscopy and data are available for download. These data should open up new perspectives on the significant role of proteins while combating external and internal fluctuations.

Get3 is a holdase chaperone and moves to deposition sites for aggregated proteins when membrane targeting is blocked.

The endomembrane system of yeast contains different tail-anchored proteins that are post-translationally targeted to membranes via their C-terminal transmembrane domain. This hydrophobic segment could be hazardous in the cytosol if membrane insertion fails, resulting in the need for energy-dependent chaperoning and the degradation of aggregated tail-anchored proteins. A cascade of GET proteins cooperates in a conserved pathway to accept newly synthesized tail-anchored proteins from ribosomes and guide them to a receptor at the endoplasmic reticulum, where membrane integration takes place. It is, however, unclear how the GET system reacts to conditions of energy depletion that might prevent membrane insertion and hence lead to the accumulation of hydrophobic proteins in the cytosol. Here we show that the ATPase Get3, which accommodates the hydrophobic tail anchor of clients, has a dual function: promoting tail-anchored protein insertion when glucose is abundant and serving as an ATP-independent holdase chaperone during energy depletion. Like the generic chaperones Hsp42, Ssa2, Sis1 and Hsp104, we found that Get3 moves reversibly to deposition sites for protein aggregates, hence supporting the sequestration of tail-anchored proteins under conditions that prevent tail-anchored protein insertion. Our findings support a ubiquitous role for the cytosolic GET complex as a triaging platform involved in cellular proteostasis.

Interactions of subunit CCT3 in the yeast chaperonin CCT/TRiC with Q/N-rich proteins revealed by high-throughput microscopy analysis.

The eukaryotic chaperonin containing t-complex polypeptide 1 (CCT/TRiC) is an ATP-fueled machine that assists protein folding. It consists of two back-to-back stacked rings formed by eight different subunits that are arranged in a fixed permutation. The different subunits of CCT are believed to possess unique substrate binding specificities that are still mostly unknown. Here, we used high-throughput microscopy analysis of yeast cells to determine changes in protein levels and localization as a result of a Glu to Asp mutation in the ATP binding site of subunits 3 (CCT3) or 6 (CCT6). The mutation in subunit CCT3 was found to induce cytoplasmic foci termed P-bodies where mRNAs, which are not translated, accumulate and can be degraded. Analysis of the changes in protein levels and structural modeling indicate that P-body formation in cells with the mutation in CCT3 is linked to the specific interaction of this subunit with Gln/Asn-rich segments that are enriched in many P-body proteins. An in vitro gel-shift analysis was used to show that the mutation in subunit CCT3 interferes with the ability of CCT to bind a Gln/Asn-rich protein aggregate. More generally, the strategy used in this work can be used to unravel the substrate specificities of other chaperone systems.

Validated Bayesian Differentiation of Causative and Passenger Mutations.

In many contexts, the problem arises of determining which of many candidate mutations is the most likely to be causative for some phenotype. It is desirable to have a way to evaluate this probability that relies as little as possible on previous knowledge, to avoid bias against discovering new genes or functions. We have isolated mutants with blocked cell cycle progression in Chlamydomonas and determined mutant genome sequences. Due to the intensity of UV mutagenesis required for efficient mutant collection, the mutants contain multiple mutations altering coding sequence. To provide a quantitative estimate of probability that each individual mutation in a given mutant is the causative one, we developed a Bayesian approach. The approach employs four independent indicators: sequence conservation of the mutated coding sequence with Arabidopsis; severity of the mutation relative to Chlamydomonas wild-type based on Blosum62 scores; meiotic mapping information for location of the causative mutation relative to known molecular markers; and, for a subset of mutants, the transcriptional profile of the candidate wild-type genes through the mitotic cell cycle. These indicators are statistically independent, and so can be combined quantitatively into a single probability calculation. We validate this calculation: recently isolated mutations that were not in the training set for developing the indicators, with high calculated probability of causality, are confirmed in every case by additional genetic data to indeed be causative. Analysis of "best reciprocal BLAST" (BRB) relationships among Chlamydomonas and other eukaryotes indicate that the temperature sensitive-lethal (Ts-lethal) mutants that our procedure recovers are highly enriched for fundamental cell-essential functions conserved broadly across plants and other eukaryotes, accounting for the high information content of sequence alignment to Arabidopsis.

High-Throughput Robotically Assisted Isolation of Temperature-sensitive Lethal Mutants in Chlamydomonas reinhardtii.

Systematic identification and characterization of genetic perturbations have proven useful to decipher gene function and cellular pathways. However, the conventional approaches of permanent gene deletion cannot be applied to essential genes. We have pioneered a unique collection of ~70 temperature-sensitive (ts) lethal mutants for studying cell cycle regulation in the unicellular green algae Chlamydomonas reinhardtii1. These mutations identify essential genes, and the ts alleles can be conditionally inactivated by temperature shift, providing valuable tools to identify and analyze essential functions. Mutant collections are much more valuable if they are close to comprehensive, since scattershot collections can miss important components. However, this requires the efficient collection of a large number of mutants, especially in a wide-target screen. Here, we describe a robotics-based pipeline for generating ts lethal mutants and analyzing their phenotype in Chlamydomonas. This technique can be applied to any microorganism that grows on agar. We have collected over 3000 ts mutants, probably including mutations in most or all cell-essential pathways, including about 200 new candidate cell cycle mutations. Subsequent molecular and cellular characterization of these mutants should provide new insights in plant cell biology; a comprehensive mutant collection is an essential prerequisite to ensure coverage of a broad range of biological pathways. These methods are integrated with downstream genetics and bioinformatics procedures for efficient mapping and identification of the causative mutations that are beyond the scope of this manuscript.

Affinity and competition for TBP are molecular determinants of gene expression noise.

Cell-to-cell variation in gene expression levels (noise) generates phenotypic diversity and is an important phenomenon in evolution, development and disease. TATA-box binding protein (TBP) is an essential factor that is required at virtually every eukaryotic promoter to initiate transcription. While the presence of a TATA-box motif in the promoter has been strongly linked with noise, the molecular mechanism driving this relationship is less well understood. Through an integrated analysis of multiple large-scale data sets, computer simulation and experimental validation in yeast, we provide molecular insights into how noise arises as an emergent property of variable binding affinity of TBP for different promoter sequences, competition between interaction partners to bind the same surface on TBP (to either promote or disrupt transcription initiation) and variable residence times of TBP complexes at a promoter. These determinants may be fine-tuned under different conditions and during evolution to modulate eukaryotic gene expression noise.

A novel single-cell screening platform reveals proteome plasticity during yeast stress responses.

Uncovering the mechanisms underlying robust responses of cells to stress is crucial for our understanding of cellular physiology. Indeed, vast amounts of data have been collected on transcriptional responses in Saccharomyces cerevisiae. However, only a handful of pioneering studies describe the dynamics of proteins in response to external stimuli, despite the fact that regulation of protein levels and localization is an essential part of such responses. Here we characterized unprecedented proteome plasticity by systematically tracking the localization and abundance of 5,330 yeast proteins at single-cell resolution under three different stress conditions (DTT, H2O2, and nitrogen starvation) using the GFP-tagged yeast library. We uncovered a unique "fingerprint" of changes for each stress and elucidated a new response arsenal for adapting to radical environments. These include bet-hedging strategies, organelle rearrangement, and redistribution of protein localizations. All data are available for download through our online database, LOQATE (localization and quantitation atlas of yeast proteome).

Formation and dissociation of proteasome storage granules are regulated by cytosolic pH.

The 26S proteasome is the major protein degradation machinery of the cell and is regulated at many levels. One mode of regulation involves accumulation of proteasomes in proteasome storage granules (PSGs) upon glucose depletion. Using a systematic robotic screening approach in yeast, we identify trans-acting proteins that regulate the accumulation of proteasomes in PSGs. Our dataset was enriched for subunits of the vacuolar adenosine triphosphatase (V-ATPase) complex, a proton pump required for vacuole acidification. We show that the impaired ability of V-ATPase mutants to properly govern intracellular pH affects the kinetics of PSG formation. We further show that formation of other protein aggregates upon carbon depletion also is triggered in mutants with impaired activity of the plasma membrane proton pump and the V-ATPase complex. We thus identify cytosolic pH as a specific cellular signal involved both in the glucose sensing that mediates PSG formation and in a more general mechanism for signaling carbon source exhaustion.

Explorations in topology-delving underneath the surface of genetic interaction maps.

High throughput assays, as well as advances in computational approaches, have recently allowed the acquisition of vast amounts of genetic interaction (GI) data in several organisms. Since GIs are a functional measure that reports on the effect of a mutation in one gene on the phenotype of a mutation in another, they can serve as a powerful tool to study both the function of individual genes and the wiring of biological networks. Therefore, these data hold much promise for advancing our understanding of cellular systems. In this review we focus on the methodologies currently available for using and interpreting large datasets of GIs for functional gene groups (GI maps), and elaborate on the challenges ahead. In addition, we discuss potential applications for the study of evolution and disease mechanisms, and highlight the need for comprehensive integrative analysis to extract the wealth of information found in these maps.