Systems Analysis of the Response of Photosynthesis, Metabolism, and Growth to an Increase in Irradiance in the Photosynthetic Model Organism Chlamydomonas reinhardtii.

We investigated the systems response of metabolism and growth after an increase in irradiance in the nonsaturating range in the algal model Chlamydomonas reinhardtii. In a three-step process, photosynthesis and the levels of metabolites increased immediately, growth increased after 10 to 15 min, and transcript and protein abundance responded by 40 and 120 to 240 min, respectively. In the first phase, starch and metabolites provided a transient buffer for carbon until growth increased. This uncouples photosynthesis from growth in a fluctuating light environment. In the first and second phases, rising metabolite levels and increased polysome loading drove an increase in fluxes. Most Calvin-Benson cycle (CBC) enzymes were substrate-limited in vivo, and strikingly, many were present at higher concentrations than their substrates, explaining how rising metabolite levels stimulate CBC flux. Rubisco, fructose-1,6-biosphosphatase, and seduheptulose-1,7-bisphosphatase were close to substrate saturation in vivo, and flux was increased by posttranslational activation. In the third phase, changes in abundance of particular proteins, including increases in plastidial ATP synthase and some CBC enzymes, relieved potential bottlenecks and readjusted protein allocation between different processes. Despite reasonable overall agreement between changes in transcript and protein abundance (R2 = 0.24), many proteins, including those in photosynthesis, changed independently of transcript abundance.

Lipid biosynthesis and protein concentration respond uniquely to phosphate supply during leaf development in highly phosphorus-efficient Hakea prostrata.

Hakea prostrata (Proteaceae) is adapted to severely phosphorus-impoverished soils and extensively replaces phospholipids during leaf development. We investigated how polar lipid profiles change during leaf development and in response to external phosphate supply. Leaf size was unaffected by a moderate increase in phosphate supply. However, leaf protein concentration increased by more than 2-fold in young and mature leaves, indicating that phosphate stimulates protein synthesis. Orthologs of known lipid-remodeling genes in Arabidopsis (Arabidopsis thaliana) were identified in the H. prostrata transcriptome. Their transcript profiles in young and mature leaves were analyzed in response to phosphate supply alongside changes in polar lipid fractions. In young leaves of phosphate-limited plants, phosphatidylcholine/phosphatidylethanolamine and associated transcript levels were higher, while phosphatidylglycerol and sulfolipid levels were lower than in mature leaves, consistent with low photosynthetic rates and delayed chloroplast development. Phosphate reduced galactolipid and increased phospholipid concentrations in mature leaves, with concomitant changes in the expression of only four H. prostrata genes, GLYCEROPHOSPHODIESTER PHOSPHODIESTERASE1, N-METHYLTRANSFERASE2, NONSPECIFIC PHOSPHOLIPASE C4, and MONOGALACTOSYLDIACYLGLYCEROL3. Remarkably, phosphatidylglycerol levels decreased with increasing phosphate supply and were associated with lower photosynthetic rates. Levels of polar lipids with highly unsaturated 32:x (x = number of double bonds in hydrocarbon chain) and 34:x acyl chains increased. We conclude that a regulatory network with a small number of central hubs underpins extensive phospholipid replacement during leaf development in H. prostrata. This hard-wired regulatory framework allows increased photosynthetic phosphorus use efficiency and growth in a low-phosphate environment. This may have rendered H. prostrata lipid metabolism unable to adjust to higher internal phosphate concentrations.

A step-by-step protocol for formaldehyde-assisted isolation of regulatory elements from Arabidopsis thaliana.

The control of gene expression by transcriptional regulators and other types of functionally relevant DNA transactions such as chromatin remodeling and replication underlie a vast spectrum of biological processes in all organisms. DNA transactions require the controlled interaction of proteins with DNA sequence motifs which are often located in nucleosome-depleted regions (NDRs) of the chromatin. Formaldehyde-assisted isolation of regulatory elements (FAIRE) has been established as an easy-to-implement method for the isolation of NDRs from a number of eukaryotic organisms, and it has been successfully employed for the discovery of new regulatory segments in genomic DNA from, for example, yeast, Drosophila, and humans. Until today, however, FAIRE has only rarely been employed in plant research and currently no detailed FAIRE protocol for plants has been published. Here, we provide a step-by-step FAIRE protocol for NDR discovery in Arabidopsis thaliana. We demonstrate that NDRs isolated from plant chromatin are readily amenable to quantitative polymerase chain reaction and next-generation sequencing. Only minor modification of the FAIRE protocol will be needed to adapt it to other plants, thus facilitating the global inventory of regulatory regions across species.

Combined transcription factor profiling, microarray analysis and metabolite profiling reveals the transcriptional control of metabolic shifts occurring during tomato fruit development.

Maturation of fleshy fruits such as tomato (Solanum lycopersicum) is subject to tight genetic control. Here we describe the development of a quantitative real-time PCR platform that allows accurate quantification of the expression level of approximately 1000 tomato transcription factors. In addition to utilizing this novel approach, we performed cDNA microarray analysis and metabolite profiling of primary and secondary metabolites using GC-MS and LC-MS, respectively. We applied these platforms to pericarp material harvested throughout fruit development, studying both wild-type Solanum lycopersicum cv. Ailsa Craig and the hp1 mutant. This mutant is functionally deficient in the tomato homologue of the negative regulator of the light signal transduction gene DDB1 from Arabidopsis, and is furthermore characterized by dramatically increased pigment and phenolic contents. We choose this particular mutant as it had previously been shown to have dramatic alterations in the content of several important fruit metabolites but relatively little impact on other ripening phenotypes. The combined dataset was mined in order to identify metabolites that were under the control of these transcription factors, and, where possible, the respective transcriptional regulation underlying this control. The results are discussed in terms of both programmed fruit ripening and development and the transcriptional and metabolic shifts that occur in parallel during these processes.

Construction and evaluation of a whole genome microarray of Chlamydomonas reinhardtii.

BACKGROUND: Chlamydomonas reinhardtii is widely accepted as a model organism regarding photosynthesis, circadian rhythm, cell mobility, phototaxis, and biotechnology. The complete annotation of the genome allows transcriptomic studies, however a new microarray platform was needed. Based on the completed annotation of Chlamydomonas reinhardtii a new microarray on an Agilent platform was designed using an extended JGI 3.1 genome data set which included 15000 transcript models. RESULTS: In total 44000 probes were determined (3 independent probes per transcript model) covering 93% of the transcriptome. Alignment studies with the recently published AUGUSTUS 10.2 annotation confirmed 11000 transcript models resulting in a very good coverage of 70% of the transcriptome (17000). Following the estimation of 10000 predicted genes in Chlamydomonas reinhardtii our new microarray, nevertheless, covers the expected genome by 90-95%. CONCLUSIONS: To demonstrate the capabilities of the new microarray, we analyzed transcript levels for cultures grown under nitrogen as well as sulfate limitation, and compared the results with recently published microarray and RNA-seq data. We could thereby confirm previous results derived from data on nutrient-starvation induced gene expression of a group of genes related to protein transport and adaptation of the metabolism as well as genes related to efficient light harvesting, light energy distribution and photosynthetic electron transport.

A growth phenotyping pipeline for Arabidopsis thaliana integrating image analysis and rosette area modeling for robust quantification of genotype effects.

• To gain a deeper understanding of the mechanisms behind biomass accumulation, it is important to study plant growth behavior. Manually phenotyping large sets of plants requires important human resources and expertise and is typically not feasible for detection of weak growth phenotypes. Here, we established an automated growth phenotyping pipeline for Arabidopsis thaliana to aid researchers in comparing growth behaviors of different genotypes. • The analysis pipeline includes automated image analysis of two-dimensional digital plant images and evaluation of manually annotated information of growth stages. It employs linear mixed-effects models to quantify genotype effects on total rosette area and relative leaf growth rate (RLGR) and ANOVAs to quantify effects on developmental times. • Using the system, a single researcher can phenotype up to 7000 plants d⁻¹. Technical variance is very low (typically < 2%). We show quantitative results for the growth-impaired starch-excess mutant sex4-3 and the growth-enhanced mutant grf9. • We show that recordings of environmental and developmental variables reduce noise levels in the phenotyping datasets significantly and that careful examination of predictor variables (such as d after sowing or germination) is crucial to avoid exaggerations of recorded phenotypes and thus biased conclusions.

QuantPrime--a flexible tool for reliable high-throughput primer design for quantitative PCR.

BACKGROUND: Medium- to large-scale expression profiling using quantitative polymerase chain reaction (qPCR) assays are becoming increasingly important in genomics research. A major bottleneck in experiment preparation is the design of specific primer pairs, where researchers have to make several informed choices, often outside their area of expertise. Using currently available primer design tools, several interactive decisions have to be made, resulting in lengthy design processes with varying qualities of the assays. RESULTS: Here we present QuantPrime, an intuitive and user-friendly, fully automated tool for primer pair design in small- to large-scale qPCR analyses. QuantPrime can be used online through the internet http://www.quantprime.de/ or on a local computer after download; it offers design and specificity checking with highly customizable parameters and is ready to use with many publicly available transcriptomes of important higher eukaryotic model organisms and plant crops (currently 295 species in total), while benefiting from exon-intron border and alternative splice variant information in available genome annotations. Experimental results with the model plant Arabidopsis thaliana, the crop Hordeum vulgare and the model green alga Chlamydomonas reinhardtii show success rates of designed primer pairs exceeding 96%. CONCLUSION: QuantPrime constitutes a flexible, fully automated web application for reliable primer design for use in larger qPCR experiments, as proven by experimental data. The flexible framework is also open for simple use in other quantification applications, such as hydrolyzation probe design for qPCR and oligonucleotide probe design for quantitative in situ hybridization. Future suggestions made by users can be easily implemented, thus allowing QuantPrime to be developed into a broad-range platform for the design of RNA expression assays.

Species Identification in Malaise Trap Samples by DNA Barcoding Based on NGS Technologies and a Scoring Matrix.

The German Barcoding initiatives BFB and GBOL have generated a reference library of more than 16,000 metazoan species, which is now ready for applications concerning next generation molecular biodiversity assessments. To streamline the barcoding process, we have developed a meta-barcoding pipeline: We pre-sorted a single malaise trap sample (obtained during one week in August 2014, southern Germany) into 12 arthropod orders and extracted DNA from pooled individuals of each order separately, in order to facilitate DNA extraction and avoid time consuming single specimen selection. Aliquots of each ordinal-level DNA extract were combined to roughly simulate a DNA extract from a non-sorted malaise sample. Each DNA extract was amplified using four primer sets targeting the CO1-5' fragment. The resulting PCR products (150-400bp) were sequenced separately on an Illumina Mi-SEQ platform, resulting in 1.5 million sequences and 5,500 clusters (coverage ≥10; CD-HIT-EST, 98%). Using a total of 120,000 DNA barcodes of identified, Central European Hymenoptera, Coleoptera, Diptera, and Lepidoptera downloaded from BOLD we established a reference sequence database for a local CUSTOM BLAST. This allowed us to identify 529 Barcode Index Numbers (BINs) from our sequence clusters derived from pooled Malaise trap samples. We introduce a scoring matrix based on the sequence match percentages of each amplicon in order to gain plausibility for each detected BIN, leading to 390 high score BINs in the sorted samples; whereas 268 of these high score BINs (69%) could be identified in the combined sample. The results indicate that a time consuming presorting process will yield approximately 30% more high score BINs compared to the non-sorted sample in our case. These promising results indicate that a fast, efficient and reliable analysis of next generation data from malaise trap samples can be achieved using this pipeline.

Genome-wide identification of regulatory elements and reconstruction of gene regulatory networks of the green alga Chlamydomonas reinhardtii under carbon deprivation.

The unicellular green alga Chlamydomonas reinhardtii is a long-established model organism for studies on photosynthesis and carbon metabolism-related physiology. Under conditions of air-level carbon dioxide concentration [CO2], a carbon concentrating mechanism (CCM) is induced to facilitate cellular carbon uptake. CCM increases the availability of carbon dioxide at the site of cellular carbon fixation. To improve our understanding of the transcriptional control of the CCM, we employed FAIRE-seq (formaldehyde-assisted Isolation of Regulatory Elements, followed by deep sequencing) to determine nucleosome-depleted chromatin regions of algal cells subjected to carbon deprivation. Our FAIRE data recapitulated the positions of known regulatory elements in the promoter of the periplasmic carbonic anhydrase (Cah1) gene, which is upregulated during CCM induction, and revealed new candidate regulatory elements at a genome-wide scale. In addition, time series expression patterns of 130 transcription factor (TF) and transcription regulator (TR) genes were obtained for cells cultured under photoautotrophic condition and subjected to a shift from high to low [CO2]. Groups of co-expressed genes were identified and a putative directed gene-regulatory network underlying the CCM was reconstructed from the gene expression data using the recently developed IOTA (inner composition alignment) method. Among the candidate regulatory genes, two members of the MYB-related TF family, Lcr1 (Low-CO 2 response regulator 1) and Lcr2 (Low-CO2 response regulator 2), may play an important role in down-regulating the expression of a particular set of TF and TR genes in response to low [CO2]. The results obtained provide new insights into the transcriptional control of the CCM and revealed more than 60 new candidate regulatory genes. Deep sequencing of nucleosome-depleted genomic regions indicated the presence of new, previously unknown regulatory elements in the C. reinhardtii genome. Our work can serve as a basis for future functional studies of transcriptional regulator genes and genomic regulatory elements in Chlamydomonas.

A major quantitative trait locus for cadmium tolerance in Arabidopsis halleri colocalizes with HMA4, a gene encoding a heavy metal ATPase.

Cadmium (Cd) tolerance seems to be a constitutive species-level trait in Arabidopsis halleri sp. halleri. Therefore, an interspecific cross was made between A. halleri and its closest nontolerant interfertile relative, Arabidopsis lyrata sp. petraea, and a first-generation backcross population (BC1) was used to map quantitative trait loci (QTL) for Cd tolerance. Three QTL were identified, which explained 43%, 24%, and 16% of the phenotypic variation in the mapping population. Heavy metal transporting ATPases4 (HMA4), encoding a predicted heavy metal ATPase, colocalized with the peak of the major QTL Cdtol-1 and was consequently further studied. HMA4 transcripts levels were higher in the roots and the shoots of A. halleri than in A. lyrata sp. petraea. Furthermore, HMA4 was also more highly expressed in all BC1 genotypes harboring the HMA4 A. halleri allele at the QTL Cdtol-1, independently of the presence of an A. halleri allele at the two other QTL. Overexpression of AhHMA4 in yeast (Saccharomyces cerevisiae) supported a role of HMA4 in zinc (Zn) and Cd transport by reducing the Cd and Zn contents of the yeast cells. In epidermal tobacco (Nicotiana tabacum) cells, AhHMA4:green fluorescent protein was clearly localized in the plasma membrane. Taken together, all available data point to the elevated expression of HMA4 P(1B)-type ATPase as an efficient mechanism for improving Cd/Zn tolerance in plants under conditions of Cd/Zn excess by maintaining low cellular Cd(2+) and Zn(2+) concentrations in the cytoplasm.