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The technological advancements in bio-science research are resulting in the generation of vast amounts of complex and heterogeneous data sets from individual studies. Efficient Research Data Management solutions based on FAIR principles can guide the research groups toward standardizing and packaging the study-specific research results into uniquely identifiable digital objects that are easily traceable and identifiable, leading to knowledge discovery, collaboration, and innovation. However, to explore the inter-dependencies among data sets originating from different study disciplines, it is crucial to deploy a generic data-centric RDM solution that overcomes inherent challenges and helps manage complex data sets. This solution should respect participating groups' data and security policies while providing an integrated data view. In this paper, we introduce ARC Registry, a cloud-native search & exploration application that integrates experimental metadata from individual research groups that have deployed PLANTdataHUB (FAIR-RDM) solution. The focus is on the parts of PLANTdataHUB and ARC Registry that facilitate near-real-time integration of experimental metadata from standardized digital objects (Annotated Research Contexts) across participating research groups. [ABSTRACT FROM AUTHOR]

SUMMARY: Plant acclimation to an ever‐changing environment is decisive for growth, reproduction, and survival. Light availability limits biomass production on both ends of the intensity spectrum. Therefore, the adjustment of plant metabolism is central to high‐light (HL) acclimation, and the accumulation of photoprotective anthocyanins is commonly observed. However, mechanisms and factors regulating the HL acclimation response are less clear. Two Arabidopsis mutants of spliceosome components exhibiting a pronounced anthocyanin overaccumulation in HL were isolated from a forward genetic screen for new factors crucial for plant acclimation. Time‐resolved physiological, transcriptome, and metabolome analysis revealed a vital function of the spliceosome components for rapidly adjusting gene expression and metabolism. Deficiency of INCREASED LEVEL OF POLYPLOIDY1 (ILP1), NTC‐RELATED PROTEIN1 (NTR1), and PLEIOTROPIC REGULATORY LOCUS1 (PRL1) resulted in a marked overaccumulation of carbohydrates and strongly diminished amino acid biosynthesis in HL. While not generally limited in N‐assimilation, ilp1, ntr1, and prl1 showed higher glutamate levels and reduced amino acid biosynthesis in HL. The comprehensive analysis reveals a function of the spliceosome components in the conditional regulation of the carbon:nitrogen balance and the accumulation of anthocyanins during HL acclimation. The importance of gene expression, metabolic regulation, and re‐direction of carbon towards anthocyanin biosynthesis for HL acclimation are discussed. Significance Statement: Spliceosomal components are required for high‐light acclimation. [ABSTRACT FROM AUTHOR]

High temperatures impair plant growth and reduce agricultural yields, but the underlying mechanisms remain elusive. The unicellular green alga Chlamydomonas reinhardtii is an excellent model to study heat responses in photosynthetic cells due to its fast growth rate, many similarities in cellular processes to land plants, simple and sequenced genome, and ample genetic and genomics resources. Chlamydomonas grows in light by photosynthesis and with externally supplied acetate as an organic carbon source. Understanding how organic carbon sources affect heat responses is important for the algal industry but remains understudied. We cultivated wild-type Chlamydomonas under highly controlled conditions in photobioreactors at 25 °C (control), 35 °C (moderate high temperature), or 40 °C (acute high temperature) with or without constant acetate supply for 1 or 4 day. Treatment at 35 °C increased algal growth with constant acetate supply but reduced algal growth without sufficient acetate. The overlooked and dynamic effects of 35 °C could be explained by induced acetate uptake and metabolism. Heat treatment at 40 °C for more than 2 day was lethal to algal cultures with or without constant acetate supply. Our findings provide insights to understand algal heat responses and help improve thermotolerance in photosynthetic cells. [ABSTRACT FROM AUTHOR]

Motivation: Within the frame of their genetic capacity, organisms are able to modify their molecular state to cope with changing environmental conditions or induced genetic disposition. As high throughput methods are becoming increasingly affordable, time series analysis techniques are applied frequently to study the complex dynamic interplay between genes, proteins, and metabolites at the physiological and molecular level. Common analysis approaches fail to simultaneously include (i) information about the replicate variance and (ii) the limited number of responses/shapes that a biological system is typically able to take. Results: We present a novel approach to model and classify short time series signals, conceptually based on a classical time series analysis, where the dependency of the consecutive time points is exploited. Constrained spline regression with automated model selection separates between noise and signal under the assumption that highly frequent changes are less likely to occur, simultaneously preserving information about the detected variance. This enables a more precise representation of the measured information and improves temporal classification in order to identify biologically interpretable correlations among the data. Availability and implementation: An open source F# implementation of the presented method and documentation of its usage is freely available in the TempClass repository, https://github.com/CSBiology/TempClass [58]. [ABSTRACT FROM AUTHOR]

SUMMARY: In modern reproducible, hypothesis‐driven plant research, scientists are increasingly relying on research data management (RDM) services and infrastructures to streamline the processes of collecting, processing, sharing, and archiving research data. FAIR (i.e., findable, accessible, interoperable, and reusable) research data play a pivotal role in enabling the integration of interdisciplinary knowledge and facilitating the comparison and synthesis of a wide range of analytical findings. The PLANTdataHUB offers a solution that realizes RDM of scientific (meta)data as evolving collections of files in a directory – yielding FAIR digital objects called ARCs – with tools that enable scientists to plan, communicate, collaborate, publish, and reuse data on the same platform while gaining continuous quality control insights. The centralized platform is scalable from personal use to global communities and provides advanced federation capabilities for institutions that prefer to host their own satellite instances. This approach borrows many concepts from software development and adapts them to fit the challenges of the field of modern plant science undergoing digital transformation. The PLANTdataHUB supports researchers in each stage of a scientific project with adaptable continuous quality control insights, from the early planning phase to data publication. The central live instance of PLANTdataHUB is accessible at (https://git.nfdi4plants.org), and it will continue to evolve as a community‐driven and dynamic resource that serves the needs of contemporary plant science. Significance Statement: PLANTdataHUB fills a gap in the RDM ecosystem for plant research by providing (a) a resource for plant researchers to collaboratively conduct FAIR‐by‐design research, (b) a blueprint for custom infrastructures, with federation ability, and (c) a practical contribution to the discussion about best practices, standards, and tooling in FAIR plant research. In contrast to other similar resources, PLANTdataHUB embraces decentralization and seeks to leverage similarities to open‐source software development and best practices identified there. [ABSTRACT FROM AUTHOR]

The functionality of all metabolic processes in chloroplasts depends on a balanced integration of nuclear‐ and chloroplast‐encoded polypeptides into the plastid's proteome. The chloroplast chaperonin machinery is an essential player in chloroplast protein folding under ambient and stressful conditions, with a more intricate structure and subunit composition compared to the orthologous GroEL/ES chaperonin of Escherichia coli. However, its exact role in chloroplasts remains obscure, mainly because of very limited knowledge about the interactors. We employed the competition immunoprecipitation method for the identification of the chaperonin's interactors in Chlamydomonas reinhardtii. Co‐immunoprecipitation of the target complex in the presence of increasing amounts of isotope‐labelled competitor epitope and subsequent mass spectrometry analysis specifically allowed to distinguish true interactors from unspecifically co‐precipitated proteins. Besides known substrates such as RbcL and the expected complex partners, we revealed numerous new interactors with high confidence. Proteins that qualify as putative substrate proteins differ from bulk chloroplast proteins by a higher content of beta‐sheets, lower alpha‐helical conformation and increased aggregation propensity. Immunoprecipitations targeted against a subunit of the co‐chaperonin lid revealed the ClpP protease as a specific partner complex, pointing to a close collaboration of these machineries to maintain protein homeostasis in the chloroplast. Summary statement: We applied competition co‐immunoprecipitation to reveal the interactome of the chloroplast Cpn60 chaperonin in Chlamydomonas reinhardtii cells under ambient conditions and heat and characterised the physico‐chemical features of the proteins that are preferably bound by the folding apparatus. [ABSTRACT FROM AUTHOR]

Research data management (RDM) combines a set of practices for the organization, storage and preservation of data from research projects. The RDM strategy of a project is usually formalized as a data management plan (DMP)—a document that sets out procedures to ensure data findability, accessibility, interoperability and reusability (FAIR-ness). Many aspects of RDM are standardized across disciplines so that data and metadata are reusable, but the components of DMPs in the plant sciences are often disconnected. The inability to reuse plant-specific DMP content across projects and funding sources requires additional time and effort to write unique DMPs for different settings. To address this issue, we developed DataPLAN—an open-source tool incorporating prewritten DMP content for the plant sciences that can be used online or offline to prepare multiple DMPs. The current version of DataPLAN supports Horizon 2020 and Horizon Europe projects, as well as projects funded by the German Research Foundation (DFG). Furthermore, DataPLAN offers the option for users to customize their own templates. Additional templates to accommodate other funding schemes will be added in the future. DataPLAN reduces the workload needed to create or update DMPs in the plant sciences by presenting standardized RDM practices optimized for different funding contexts. [ABSTRACT FROM AUTHOR]

Metabolic engineering of microalgae offers a promising solution for sustainable biofuel production, and rational design of engineering strategies can be improved by employing metabolic models that integrate enzyme turnover numbers. However, the coverage of turnover numbers for Chlamydomonas reinhardtii, a model eukaryotic microalga accessible to metabolic engineering, is 17-fold smaller compared to the heterotrophic cell factory Saccharomyces cerevisiae. Here we generate quantitative protein abundance data of Chlamydomonas covering 2337 to 3708 proteins in various growth conditions to estimate in vivo maximum apparent turnover numbers. Using constrained-based modeling we provide proxies for in vivo turnover numbers of 568 reactions, representing a 10-fold increase over the in vitro data for Chlamydomonas. Integration of the in vivo estimates instead of in vitro values in a metabolic model of Chlamydomonas improved the accuracy of enzyme usage predictions. Our results help in extending the knowledge on uncharacterized enzymes and improve biotechnological applications of Chlamydomonas. Closing a major gap in photosynthetic metabolic modelling, the authors provide over 500 estimates of in vivo enzyme catalytic rate in C. reinhardtii, which considerably improves predictions on how enzyme mass is allocated to different pathways. [ABSTRACT FROM AUTHOR]

Proteins are essential macromolecules that carry out a plethora of biological functions. The thermal stability of proteins is an important property that affects their function and determines their suitability for various applications. However, current experimental approaches, primarily thermal proteome profiling, are expensive, labor-intensive, and have limited proteome and species coverage. To close the gap between available experimental data and sequence information, a novel protein thermal stability predictor called DeepSTABp has been developed. DeepSTABp uses a transformer-based protein language model for sequence embedding and state-of-the-art feature extraction in combination with other deep learning techniques for end-to-end protein melting temperature prediction. DeepSTABp can predict the thermal stability of a wide range of proteins, making it a powerful and efficient tool for large-scale prediction. The model captures the structural and biological properties that impact protein stability, and it allows for the identification of the structural features that contribute to protein stability. DeepSTABp is available to the public via a user-friendly web interface, making it accessible to researchers in various fields. [ABSTRACT FROM AUTHOR]

Studies of protein–protein interactions in membranes are very important to fully understand the biological function of a cell. The extraction of proteins from the native membrane environment is a critical step in the preparation of membrane proteins that might affect the stability of protein complexes. In this work, we used the amphiphilic diisobutylene/maleic acid copolymer to extract the membrane proteome of the opportunistic pathogen Pseudomonas aeruginosa , thereby creating a soluble membrane-protein library within a native-like lipid-bilayer environment. Size fractionation of nanodisc-embedded proteins and subsequent mass spectrometry enabled the identification of 3358 proteins. The native membrane-protein library showed a very good overall coverage compared to previous proteome data. The pattern of size fractionation indicated that protein complexes were preserved in the library. More than 20 previously described complexes, e.g. the SecYEG and Pili complexes, were identified and analyzed for coelution. Although the mass-spectrometric dataset alone did not reveal new protein complexes, combining pulldown assays with mass spectrometry was successful in identifying new protein interactions in the native membrane-protein library. Thus, we identified several candidate proteins for interactions with the membrane phosphodiesterase NbdA, a member of the c-di-GMP network. We confirmed the candidate proteins CzcR, PA4200, SadC, and PilB as novel interaction partners of NbdA using the bacterial adenylate cyclase two-hybrid assay. Taken together, this work demonstrates the usefulness of the native membrane-protein library of P. aeruginosa for the investigation of protein interactions and membrane-protein complexes. Data are available via ProteomeXchange with identifiers PXD039702 and PXD039700. [ABSTRACT FROM AUTHOR]

Different intensities of high temperatures affect the growth of photosynthetic cells in nature. To elucidate the underlying mechanisms, we cultivated the unicellular green alga Chlamydomonas reinhardtii under highly controlled photobioreactor conditions and revealed systems-wide shared and unique responses to 24-hour moderate (35°C) and acute (40°C) high temperatures and subsequent recovery at 25°C. We identified previously overlooked unique elements in response to moderate high temperature. Heat at 35°C transiently arrested the cell cycle followed by partial synchronization, up-regulated transcripts/proteins involved in gluconeogenesis/glyoxylate-cycle for carbon uptake and promoted growth. But 40°C disrupted cell division and growth. Both high temperatures induced photoprotection, while 40°C distorted thylakoid/pyrenoid ultrastructure, affected the carbon concentrating mechanism, and decreased photosynthetic efficiency. We demonstrated increased transcript/protein correlation during both heat treatments and hypothesize reduced post-transcriptional regulation during heat may help efficiently coordinate thermotolerance mechanisms. During recovery after both heat treatments, especially 40°C, transcripts/proteins related to DNA synthesis increased while those involved in photosynthetic light reactions decreased. We propose down-regulating photosynthetic light reactions during DNA replication benefits cell cycle resumption by reducing ROS production. Our results provide potential targets to increase thermotolerance in algae and crops. A systems-wide analysis of the single-cell green alga Chlamydomonas reinhardti reveals shared and unique responses to moderate and acute high temperatures using multiple-level investigation of transcriptomics, proteomics, cell physiology, photosynthetic parameters, and cellular ultrastructure. [ABSTRACT FROM AUTHOR]

Alternative splicing is a potent modifier of protein function. Stromal interaction molecule 1 (Stim1) is the essential activator of store‐operated Ca2+ entry (SOCE) triggering activation of transcription factors. Here, we characterize Stim1A, a splice variant with an additional 31 amino acid domain inserted in frame within its cytosolic domain. Prominent expression of exon A is found in astrocytes, heart, kidney, and testes. Full‐length Stim1A functions as a dominant‐negative regulator of SOCE and ICRAC, facilitating sequence‐specific fast calcium‐dependent inactivation and destabilizing gating of Orai channels. Downregulation or absence of native Stim1A results in increased SOCE. Despite reducing SOCE, Stim1A leads to increased NFAT translocation. Differential proteomics revealed an interference of Stim1A with the cAMP‐SOCE crosstalk by altered modulation of phosphodiesterase 8 (PDE8), resulting in reduced cAMP degradation and increased PIP5K activity, facilitating NFAT activation. Our study uncovers a hitherto unknown mechanism regulating NFAT activation and indicates that cell‐type‐specific splicing of Stim1 is a potent means to regulate the NFAT signalosome and cAMP‐SOCE crosstalk. SYNOPSIS: Alternative splicing of the Ca2+ regulator gene (STIM1) is able to interfere both with ion channel (ORAI) gating and with Ca2+‐cAMP crosstalk to adjust for cell‐type‐specific transcription factor activation. STIM1A is a STIM1 splice variant with an extended C‐terminal domain expressed in distinct cells and tissues.STIM1A destabilizes gating of ORAI channels.Interaction of STIM1 with PDE8 is disabled by splicing‐in of the C‐terminal domain.STIM1A increases local cAMP to stabilize the NFAT signalosome. [ABSTRACT FROM AUTHOR]

While the composition and function of the major thylakoid membrane complexes are well understood, comparatively little is known about their biogenesis. The goal of this work was to shed more light on the role of auxiliary factors in the biogenesis of photosystem II (PSII). Here we have identified the homolog of LOW PSII ACCUMULATION 2 (LPA2) in Chlamydomonas. A Chlamydomonas reinhardtii lpa2 mutant grew slower in low light, was hypersensitive to high light, and exhibited aberrant structures in thylakoid membrane stacks. Chlorophyll fluorescence (F v/ F m) was reduced by 38%. Synthesis and stability of newly made PSII core subunits D1, D2, CP43, and CP47 were not impaired. However, complexome profiling revealed that in the mutant CP43 was reduced to ~23% and D1, D2, and CP47 to ~30% of wild type levels. Levels of PSI and the cytochrome b 6 f complex were unchanged, while levels of the ATP synthase were increased by ~29%. PSII supercomplexes, dimers, and monomers were reduced to ~7%, ~26%, and ~60% of wild type levels, while RC47 was increased ~6-fold and LHCII by ~27%. We propose that LPA2 catalyses a step during PSII assembly without which PSII monomers and further assemblies become unstable and prone to degradation. The LHCI antenna was more disconnected from PSI in the lpa2 mutant, presumably as an adaptive response to reduce excitation of PSI. From the co-migration profiles of 1734 membrane-associated proteins, we identified three novel putative PSII associated proteins with potential roles in regulating PSII complex dynamics, assembly, and chlorophyll breakdown. [ABSTRACT FROM AUTHOR]

The plant vacuole recycles proteins and RNA delivered to it by autophagy. In this study, by isolating intact vacuoles from Arabidopsis plants, followed by subsequent RNA purification, and deep sequencing, we provide a comprehensive characterization of Arabidopsis vacuolar RNAome. In the vacuolar RNAome, we detected ribosomal RNAs, transfer RNAs, including those of chloroplast origin, and in addition small RNA types. As autophagy is a main mechanism for the transport of RNA to the vacuole, atg5-1 mutants deficient in autophagy were included in our analysis. We observed severely reduced amounts of most chloroplast-derived RNA species in these mutants. Comparisons with cellular RNA composition provided an indication of possible up-regulation of alternative RNA breakdown pathways. By contrast, vacuolar RNA processing and composition in plants lacking vacuolar ribonuclease 2, involved in cellular RNA homeostasis, only showed minor alterations, possibly because of the presence of further so far unknown vacuolar RNase species. Among the small RNA types, we detected mature miRNAs in all vacuolar preparations but at much lower frequency in atg5-1 , raising the possibility of a biological role for vacuolar miRNAs. [ABSTRACT FROM AUTHOR]

The study of plant-environment interactions is a multidisciplinary research field. With the emergence of quantitative large-scale and high-throughput techniques, amount and dimensionality of experimental data have strongly increased. Appropriate strategies for data storage, management, and evaluation are needed to make efficient use of experimental findings. Computational approaches of data mining are essential for deriving statistical trends and signatures contained in data matrices. Although, current biology is challenged by high data dimensionality in general, this is particularly true for plant biology. Plants as sessile organisms have to cope with environmental fluctuations. This typically results in strong dynamics of metabolite and protein concentrations which are often challenging to quantify. Summarizing experimental output results in complex data arrays, which need computational statistics and numerical methods for building quantitative models. Experimental findings need to be combined by computational models to gain a mechanistic understanding of plant metabolism. For this, bioinformatics and mathematics need to be combined with experimental setups in physiology, biochemistry, and molecular biology. This review presents and discusses concepts at the interface of experiment and computation, which are likely to shape current and future plant biology. Finally, this interface is discussed with regard to its capabilities and limitations to develop a quantitative model of plant-environment interactions. [ABSTRACT FROM AUTHOR]

Matrix targeting sequences (MTSs) direct proteins from the cytosol into mitochondria. Efficient targeting often relies on internal matrix targeting-like sequences (iMTS-Ls) which share structural features with MTSs. Predicting iMTS-Ls was tedious and required multiple tools and webservices. We present iMLP, a deep learning approach for the prediction of iMTS-Ls in protein sequences. A recurrent neural network has been trained to predict iMTS-L propensity profiles for protein sequences of interest. The iMLP predictor considerably exceeds the speed of existing approaches. Expanding on our previous work on iMTS-L prediction, we now serve an intuitive iMLP webservice available at http://iMLP.bio.uni-kl.de and a stand-alone command line tool for power user in addition. [ABSTRACT FROM AUTHOR]

Background: There is increasing evidence that Parkinson's disease (PD) might start in the gut, thus involving and compromising also the enteric nervous system (ENS). At the clinical onset of the disease the majority of dopaminergic neurons in the midbrain is already destroyed, so that the lack of early biomarkers for the disease represents a major challenge for developing timely treatment interventions. Here, we use a transgenic A30P-α-synuclein-overexpressing PD mouse model to identify appropriate candidate markers in the gut before hallmark symptoms begin to manifest. Methods: Based on a gait analysis and striatal dopamine levels, we defined 2-month-old A30P mice as pre-symptomatic (psA30P), since they are not showing any motoric impairments of the skeletal neuromuscular system and no reduced dopamine levels, but an intestinal α-synuclein pathology. Mice at this particular age were further used to analyze functional and molecular alterations in both, the gastrointestinal tract and the ENS, to identify early pathological changes. We examined the gastrointestinal motility, the molecular composition of the ENS, as well as the expression of regulating miRNAs. Moreover, we applied A30P-α-synuclein challenges in vitro to simulate PD in the ENS. Results: A retarded gut motility and early molecular dysregulations were found in the myenteric plexus of psA30P mice. We found that i.e. neurofilament light chain, vesicle-associated membrane protein 2 and calbindin 2, together with the miRNAs that regulate them, are significantly altered in the psA30P, thus representing potential biomarkers for early PD. Many of the dysregulated miRNAs found in the psA30P mice are reported to be changed in PD patients as well, either in blood, cerebrospinal fluid or brain tissue. Interestingly, the in vitro approaches delivered similar changes in the ENS cultures as seen in the transgenic animals, thus confirming the data from the mouse model. Conclusions: These findings provide an interesting and novel approach for the identification of appropriate biomarkers in men. [ABSTRACT FROM AUTHOR]

Summary: Acclimation is the capacity to adapt to environmental changes within the lifetime of an individual. This ability allows plants to cope with the continuous variation in ambient conditions to which they are exposed as sessile organisms. Because environmental changes and extremes are becoming even more pronounced due to the current period of climate change, enhancing the efficacy of plant acclimation is a promising strategy for mitigating the consequences of global warming on crop yields. At the cellular level, the chloroplast plays a central role in many acclimation responses, acting both as a sensor of environmental change and as a target of cellular acclimation responses. In this Perspective article, we outline the activities of the Green Hub consortium funded by the German Science Foundation. The main aim of this research collaboration is to understand and strategically modify the cellular networks that mediate plant acclimation to adverse environments, employing Arabidopsis, tobacco (Nicotiana tabacum) and Chlamydomonas as model organisms. These efforts will contribute to 'smart breeding' methods designed to create crop plants with improved acclimation properties. To this end, the model oilseed crop Camelina sativa is being used to test modulators of acclimation for their potential to enhance crop yield under adverse environmental conditions. Here we highlight the current state of research on the role of gene expression, metabolism and signalling in acclimation, with a focus on chloroplast‐related processes. In addition, further approaches to uncovering acclimation mechanisms derived from systems and computational biology, as well as adaptive laboratory evolution with photosynthetic microbes, are highlighted. [ABSTRACT FROM AUTHOR]

Background: Cold stress causes dynamic changes in gene expression that are partially caused by small non-coding RNAs since they regulate protein coding transcripts and act in epigenetic gene silencing pathways. Thus, a detailed analysis of transcriptional changes of small RNAs (sRNAs) belonging to all known sRNA classes such as microRNAs (miRNA) and small interfering RNA (siRNAs) in response to cold contributes to an understanding of cold-related transcriptome changes. Result: We subjected A. thaliana plants to cold acclimation conditions (4 °C) and analyzed the sRNA transcriptomes after 3 h, 6 h and 2 d. We found 93 cold responsive differentially expressed miRNAs and only 14 of these were previously shown to be cold responsive. We performed miRNA target prediction for all differentially expressed miRNAs and a GO analysis revealed the overrepresentation of miRNA-targeted transcripts that code for proteins acting in transcriptional regulation. We also identified a large number of differentially expressed cis- and trans-nat-siRNAs, as well as sRNAs that are derived from long non-coding RNAs. By combining the results of sRNA and mRNA profiling with miRNA target predictions and publicly available information on transcription factors, we reconstructed a cold-specific, miRNA and transcription factor dependent gene regulatory network. We verified the validity of links in the network by testing its ability to predict target gene expression under cold acclimation. Conclusion: In A. thaliana, miRNAs and sRNAs derived from cis- and trans-NAT gene pairs and sRNAs derived from lncRNAs play an important role in regulating gene expression in cold acclimation conditions. This study provides a fundamental database to deepen our knowledge and understanding of regulatory networks in cold acclimation. [ABSTRACT FROM AUTHOR]

The productivity of plants and microalgae needs to be increased to feed the growing world population and to promote the development of a low-carbon economy. This goal can be achieved by improving photosynthesis via genetic engineering. In this study, we have employed the Modular Cloning strategy to overexpress the Calvin-Benson cycle (CBC) enzyme sedoheptulose-1,7-bisphosphatase (SBP1) up to threefold in the unicellular green alga Chlamydomonas reinhardtii. The protein derived from the nuclear transgene represented ∼0.3% of total cell protein. Photosynthetic rate and growth were significantly increased in SBP1-overexpressing lines under high-light and elevated CO2 conditions. Absolute quantification of the abundance of all other CBC enzymes by the QconCAT approach revealed no consistent differences between SBP1-overexpressing lines and the recipient strain. This analysis also revealed that the 11 CBC enzymes represent 11.9% of total cell protein in Chlamydomonas. Here, the range of concentrations of CBC enzymes turned out to be much larger than estimated earlier, with a 128-fold difference between the most abundant CBC protein (rbcL) and the least abundant (triose phosphate isomerase). Accordingly, the concentrations of the CBC intermediates are often but not always higher than the binding site concentrations of the enzymes for which they act as substrates. The enzymes with highest substrate to binding site ratios might represent good candidates for overexpression in subsequent engineering steps. [ABSTRACT FROM AUTHOR]

Transcription, translation, and turnover of transcripts and proteins are essential for cellular function. The contribution of those factors to protein levels is under debate, as transcript levels and cognate protein levels do not necessarily correlate due to regulation of translation and protein turnover. Here we propose neuronal polarity as a third factor that is particularly evident in the CNS, leading to considerable distances between somata and axon terminals. Consequently, transcript levels may negatively correlate with cognate protein levels in CNS regions, i.e., transcript and protein levels behave reciprocally. To test this hypothesis, we performed an integrative inter‐omics study and analyzed three interconnected rat auditory brainstem regions (cochlear nuclear complex, CN; superior olivary complex, SOC; inferior colliculus, IC) and the rest of the brain as a reference. We obtained transcript and protein sets in these regions of interest (ROIs) by DNA microarrays and label‐free mass spectrometry, and performed principal component and correlation analyses. We found 508 transcript|protein pairs and detected poor to moderate transcript|protein correlation in all ROIs, as evidenced by coefficients of determination from 0.34 to 0.54. We identified 57‐80 negatively correlating gene products in the ROIs and intensively analyzed four of them for which the correlation was poorest. Three cognate proteins (Slc6a11, Syngr1, Tppp) were synaptic and hence candidates for a negative correlation because of protein transport into axon terminals. Thus, we systematically analyzed the negatively correlating gene products. Gene ontology analyses revealed overrepresented transport/synapse‐related proteins, supporting our hypothesis. We present 30 synapse/transport‐related proteins with poor transcript|protein correlation. In conclusion, our analyses support that protein transport in polar cells is a third factor that influences the protein level and, thereby, the transcript|protein correlation. Open science badges: This article has received a badge for *Open Materials* and *Open Data* because it provided all relevant information to reproduce the study in the manuscript and because it made the data publicly available. The data can be accessed at https://osf.io/ha28n/. The complete Open Science Disclosure form for this article can be found at the end of the article. More information about the Open Practices badges can be found at https://cos.io/our-services/open-science-badges/. [ABSTRACT FROM AUTHOR]

Targeted mass spectrometry has become the method of choice to gain absolute quantification information of high quality, which is essential for a quantitative understanding of biological systems. However, the design of absolute protein quantification assays remains challenging due to variations in peptide observability and incomplete knowledge about factors influencing peptide detectability. Here, we present a deep learning algorithm for peptide detectability prediction, d::pPop, which allows the informed selection of synthetic proteotypic peptides for the successful design of targeted proteomics quantification assays. The deep neural network is able to learn a regression model that relates the physicochemical properties of a peptide to its ion intensity detected by mass spectrometry. The approach makes use of experimentally detected deviations from the assumed equimolar abundance of all peptides derived from a given protein. Trained on extensive proteomics datasets, d::pPop's plant and non-plant specific models can predict the quality of proteotypic peptides for not yet experimentally identified proteins. Interrogating the deep neural network after learning from ~76,000 peptides per model organism allows to investigate the impact of different physicochemical properties on the observability of a peptide, thus providing insights into peptide observability as a multifaceted process. Empirical evaluation with rank accuracy metrics showed that our prediction approach outperforms existing algorithms. We circumvent the delicate step of selecting positive and negative training sets and at the same time also more closely reflect the need for selecting the top most promising peptides for targeting a protein of interest. Further, we used an artificial QconCAT protein to experimentally validate the observability prediction. Our proteotypic peptide prediction approach not only facilitates the design of absolute protein quantification assays via a user-friendly web interface but also enables the selection of proteotypic peptides for not yet observed proteins, hence rendering the tool especially useful for plant research. [ABSTRACT FROM AUTHOR]

For modeling approaches in systems biology, knowledge of the absolute abundances of cellular proteins is essential. One way to gain this knowledge is the use of quantification concatamers (QconCATs), which are synthetic proteins consisting of proteotypic peptides derived from the target proteins to be quantified. The QconCAT protein is labeled with a heavy isotope upon expression in E. coli and known amounts of the purified protein are spiked into a whole cell protein extract. Upon tryptic digestion, labeled and unlabeled peptides are released from the QconCAT protein and the native proteins, respectively, and both are quantified by LC-MS/MS. The labeled Q-peptides then serve as standards for determining the absolute quantity of the native peptides/proteins. Here, we have applied the QconCAT approach to Chlamydomonas reinhardtii for the absolute quantification of the major proteins and protein complexes driving photosynthetic light reactions in the thylakoid membranes and carbon fixation in the pyrenoid. We found that with 25.2 attomol/cell the Rubisco large subunit makes up 6.6% of all proteins in a Chlamydomonas cell and with this exceeds the amount of the small subunit by a factor of 1.56. EPYC1, which links Rubisco to form the pyrenoid, is eight times less abundant than RBCS, and Rubisco activase is 32-times less abundant than RBCS. With 5.2 attomol/cell, photosystem II is the most abundant complex involved in the photosynthetic light reactions, followed by plastocyanin, photosystem I and the cytochrome b6/ f complex, which range between 2.9 and 3.5 attomol/cell. The least abundant complex is the ATP synthase with 2 attomol/cell. While applying the QconCAT approach, we have been able to identify many potential pitfalls associated with this technique. We analyze and discuss these pitfalls in detail and provide an optimized workflow for future applications of this technique. [ABSTRACT FROM AUTHOR]

Summary: The Botrytis cinerea VELVET complex regulates light‐dependent development and virulence. The goal of this study was to identify common virulence defects of several VELVET mutants and to reveal their molecular basis. Growth, differentiation, physiology, gene expression and infection of fungal strains were analyzed, and quantitative comparisons of in planta transcriptomes and secretomes were performed. VELVET mutants showed reduced release of citric acid, the major acid secreted by the wild‐type, whereas no significant role for oxalic acid was observed. Furthermore, a common set of infection‐related and secreted proteins was strongly underexpressed in the mutants. Quantitative secretome analysis with 15N metabolic labeling revealed a correlation of changes in protein and mRNA levels between wild‐type and mutants, indicating that transcript levels determine the abundance of secreted proteins. Infection sites kept at low pH partially restored lesion expansion and expression of virulence genes by the mutants. Drastic downregulation of proteases in the mutants was correlated with incomplete degradation of cellular host proteins at the infection site, but no evidence was obtained that aspartyl proteases are required for lesion formation. The B. cinerea VELVET complex controls pathogenic differentiation by regulating organic acid secretion, host tissue acidification, gene expression and protein secretion. [ABSTRACT FROM AUTHOR]

Key message: We have identified 39 proteins that interact directly or indirectly with high confidence with chloroplast HSP22E/F under heat stress thus revealing chloroplast processes affected by heat. Abstract: Under conditions promoting protein unfolding, small heat shock proteins (sHsps) prevent the irreversible aggregation of unfolding proteins by integrating into forming aggregates. Aggregates containing sHsps facilitate the access of Hsp70 and ClpB/Hsp104 chaperones, which in ATP-dependent reactions disentangle individual proteins from the aggregates and assist in their refolding to the native state. Chlamydomonas reinhardtii encodes eight different sHsps (HSP22A to H). The goal of this work was to identify chloroplast-targeted sHsps in Chlamydomonas and to obtain a comprehensive list of the substrates with which they interact during heat stress in order to understand which chloroplast processes are disturbed under heat stress. We show that HSP22E and HSP22F are major chloroplast-targeted sHsps that have emerged from a recent gene duplication event resulting from the ongoing diversification of sHsps in the Volvocales. HSP22E/F strongly accumulate during heat stress and form high molecular mass complexes. Using differential immunoprecipitation, mass spectrometry and a stringent filtering algorithm we identified 39 proteins that with high-confidence interact directly or indirectly with HSP22E/F under heat stress. We propose that the apparent thermolability of several of these proteins might be a desired trait as part of a mechanism enabling Chlamydomonas chloroplasts to rapidly react to thermal stress. [ABSTRACT FROM AUTHOR]

Biological carbon fixation is a key step in the global carbon cycle that regulates the atmosphere's compositionwhile producing the food we eat and the fuels we burn. Approximately one-third of global carbon fixation occurs in an overlooked algal organelle called the pyrenoid. The pyrenoid contains the CO2-fixing enzyme Rubisco and enhances carbon fixation by supplying Rubisco with a high concentration of CO2. Since the discovery of the pyrenoid more that 130 y ago, the molecular structure and biogenesis of this ecologically fundamental organelle have remained enigmatic. Here we use the model green alga Chlamydomonas reinhardtii to discover that a low-complexity repeat protein, Essential Pyrenoid Component 1 (EPYC1), links Rubisco to form the pyrenoid. We find that EPYC1 is of comparable abundance to Rubisco and colocalizes with Rubisco throughout the pyrenoid. We show that EPYC1 is essential for normal pyrenoid size, number, morphology, Rubisco content, and efficient carbon fixation at low CO2. We explain the central role of EPYC1 in pyrenoid biogenesis by the finding that EPYC1 binds Rubisco to form the pyrenoid matrix. We propose two models in which EPYC1's four repeats could produce the observed lattice arrangement of Rubisco in the Chlamydomonas pyrenoid. Our results suggest a surprisingly simple molecularmechanism for how Rubisco can be packaged to formthe pyrenoid matrix, potentially explaining how Rubisco packaging into a pyrenoid could have evolved across a broad range of photosynthetic eukaryotes through convergent evolution. In addition, our findings represent a key step toward engineering a pyrenoid into crops to enhance their carbon fixation efficiency. [ABSTRACT FROM AUTHOR]

Developmental or metabolic changes in chloroplasts can have profound effects on the rest of the plant cell. Such intracellular responses are associated with signals that originate in chloroplasts and convey information on their physiological status to the nucleus, which leads to large-scale changes in gene expression (retrograde signaling). A screen designed to identify components of retrograde signaling resulted in the discovery of the so-called genomes uncoupled (gun) mutants. Genetic evidence suggests that the chloroplast protein GUN1 integrates signals derived from perturbations in plastid redox state, plastid gene expression, and tetrapyrrole biosynthesis (TPB) in Arabidopsis (Arabidopsis thaliana) seedlings, exerting biogenic control of chloroplast functions. However, the molecular mechanism by which GUN1 integrates retrograde signaling in the chloroplast is unclear. Here we show that GUN1 also operates in adult plants, contributing to operational control of chloroplasts. The gun1 mutation genetically interacts with mutations of genes for the chloroplast ribosomal proteins S1 (PRPS1) and L11. Analysis of gun1 prps1 lines indicates that GUN1 controls PRPS1 accumulation at the protein level. The GUN1 protein physically interacts with proteins involved in chloroplast protein homeostasis based on coimmunoprecipitation experiments. Furthermore, yeast two-hybrid and bimolecular fluorescence complementation experiments suggest that GUN1 might transiently interact with several TPB enzymes, including Mg-chelatase subunit D (CHLD) and two other TPB enzymes known to activate retrograde signaling. Moreover, the association of PRPS1 and CHLD with protein complexes is modulated by GUN1. These findings allow us to speculate that retrograde signaling might involve GUN1-dependent formation of protein complexes. [ABSTRACT FROM AUTHOR]

Heat waves occurring at increased frequency as a consequence of global warming jeopardize crop yield safety. One way to encounter this problem is to genetically engineer crop plants toward increased thermotolerance. To identify entry points for genetic engineering, a thorough understanding of how plant cells perceive heat stress and respond to it is required. Using the unicellular green alga Chlamydomonas reinhardtii as a model system to study the fundamental mechanisms of the plant heat stress response has several advantages. Most prominent among them is the suitability of Chlamydomonas for studying stress responses system-wide and in a time-resolved manner under controlled conditions. Here we review current knowledge on how heat is sensed and signaled to trigger temporally and functionally grouped sub-responses termed response elements to prevent damage and to maintain cellular homeostasis in plant cells. [ABSTRACT FROM AUTHOR]

We applied a top-down systems biology approach to understand how Chlamydomonas reinhardtii acclimates to long-term heat stress (HS) and recovers from it. For this, we shifted cells from 25 to 42°C for 24 h and back to 25°C for ≥8 h and monitored abundances of 1856 proteins/protein groups, 99 polar and 185 lipophilic metabolites, and cytological and photosynthesis parameters. Our data indicate that acclimation of Chlamydomonas to long-term HS consists of a temporally ordered, orchestrated implementation of response elements at various system levels. These comprise (1) cell cycle arrest; (2) catabolism of larger molecules to generate compounds with roles in stress protection; (3) accumulation of molecular chaperones to restore protein homeostasis together with compatible solutes; (4) redirection of photosynthetic energy and reducing power from the Calvin cycle to the de novo synthesis of saturated fatty acids to replace polyunsaturated ones in membrane lipids, which are deposited in lipid bodies; and (5) when sinks for photosynthetic energy and reducing power are depleted, resumption of Calvin cycle activity associated with increased photorespiration, accumulation of reactive oxygen species scavengers, and throttling of linear electron flow by antenna uncoupling. During recovery from HS , cells appear to focus on processes allowing rapid resumption of growth rather than restoring pre- HS conditions. [ABSTRACT FROM AUTHOR]

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 (R  2 = 0.24), many proteins, including those in photosynthesis, changed independently of transcript abundance. [ABSTRACT FROM AUTHOR]

Plastid protein homeostasis is critical during chloroplast biogenesis and responses to changes in environmental conditions. Proteases and molecular chaperones involved in plastid protein quality control are encoded by the nucleus except for the catalytic subunit of ClpP, an evolutionarily conserved serine protease. Unlike its Escherichia coli ortholog, this chloroplast protease is essential for cell viability. To study its function, we used a recently developed system of repressible chloroplast gene expression in the alga Chlamydomonas reinhardtii. Using this repressible system, we have shown that a selective gradual depletion of ClpP leads to alteration of chloroplast morphology, causes formation of vesicles, and induces extensive cytoplasmic vacuolization that is reminiscent of autophagy. Analysis of the transcriptome and proteome during ClpP depletion revealed a set of proteins that are more abundant at the protein level, but not at the RNA level. These proteins may comprise some of the ClpP substrates. Moreover, the specific increase in accumulation, both at the RNA and protein level, of small heat shock proteins, chaperones, proteases, and proteins involved in thylakoid maintenance upon perturbation of plastid protein homeostasis suggests the existence of a chloroplast-to-nucleus signaling pathway involved in organelle quality control. We suggest that this represents a chloroplast unfolded protein response that is conceptually similar to that observed in the endoplasmic reticulum and in mitochondria. [ABSTRACT FROM AUTHOR]

Nitrogen (N) is a key nutrient that limits global primary productivity; hence, N-use efficiency is of compelling interest in agriculture and aquaculture. We used Chlamydomonas reinhardtii as a reference organism for a multicomponent analysis of the N starvation response. In the presence of acetate, respiratory metabolism is prioritized over photosynthesis; consequently, the N-sparing response targets proteins, pigments, and RNAs involved in photosynthesis and chloroplast function over those involved in respiration. Transcripts and proteins of the Calvin-Benson cycle are reduced in N-deficient cells, resulting in the accumulation of cycle metabolic intermediates. Both cytosolic and chloroplast ribosomes are reduced, but via different mechanisms, reflected by rapid changes in abundance of RNAs encoding chloroplast ribosomal proteins but not cytosolic ones. RNAs encoding transporters and enzymes for metabolizing alternative N sources increase in abundance, as is appropriate for the soil environmental niche of C. reinhardtii. Comparison of the N-replete versus N-deplete proteome indicated that abundant proteins with a high N content are reduced in N-starved cells, while the proteins that are increased have lower than average N contents. This sparing mechanism contributes to a lower cellular N/C ratio and suggests an approach for engineering increased N-use efficiency. [ABSTRACT FROM AUTHOR]

The vesicle-inducing protein in plastids (VIPP1) was suggested to play a role in thylakoid membrane formation via membrane vesicles. As this functional assignment is under debate, we investigated the function of VIPP1 in Chlamydomonas reinhardtii. Using immunofluorescence, we localized VIPP1 to distinct spots within the chloroplast. In VIPP1 -RNA interference/artificial microRNA cells, we consistently observed aberrant, prolamellar body-like structures at the origin of multiple thylakoid membrane layers, which appear to coincide with the immunofluorescent VIPP1 spots and suggest a defect in thylakoid membrane biogenesis. Accordingly, using quantitative shotgun proteomics, we found that unstressed vipp1 mutant cells accumulate 14 to 20% less photosystems, cytochrome b6f complex, and ATP synthase but 30% more light-harvesting complex II than control cells, while complex assembly, thylakoid membrane ultrastructure, and bulk lipid composition appeared unaltered. Photosystems in vipp1 mutants are sensitive to high light, which coincides with a lowered midpoint potential of the QA/QA  − redox couple and increased thermosensitivity of photosystem II (PSII), suggesting structural defects in PSII. Moreover, swollen thylakoids, despite reduced membrane energization, in vipp1 mutants grown on ammonium suggest defects in the supermolecular organization of thylakoid membrane complexes. Overall, our data suggest a role of VIPP1 in the biogenesis/assembly of thylakoid membrane core complexes, most likely by supplying structural lipids. [ABSTRACT FROM AUTHOR]

Most mitochondrial proteins are synthesized as precursors in the cytosol and post-translationally transported into mitochondria. The mitochondrial surface protein Tom70 acts at the interface of the cytosol and mitochondria. In vitro import experiments identified Tom70 as targeting receptor, particularly for hydrophobic carriers. Using in vivo methods and high-content screens, we revisit the question of Tom70 function and considerably expand the set of Tom70-dependent mitochondrial proteins. We demonstrate that the crucial activity of Tom70 is its ability to recruit cytosolic chaperones to the outer membrane. Indeed, tethering an unrelated chaperone-binding domain onto the mitochondrial surface complements most of the defects caused by Tom70 deletion. Tom70-mediated chaperone recruitment reduces the proteotoxicity of mitochondrial precursor proteins, particularly of hydrophobic inner membrane proteins. Thus, our work suggests that the predominant function of Tom70 is to tether cytosolic chaperones to the outer mitochondrial membrane, rather than to serve as a mitochondrion-specifying targeting receptor. [Display omitted] • Tom70 supports the targeting of a wide range of precursor proteins to mitochondria • In vivo , the main function of Tom70 is to recruit chaperones to the outer membrane • Small inner membrane proteins are highly toxic in the absence of Tom70 • Tom70 protects the cytosol against toxic effects of mitochondrial precursors Backes et al. identify the spectrum of substrates of the mitochondrial Tom70 receptor. Many Tom70 clients are aggregation-prone and/or membrane proteins. In vivo , the critical function of Tom70 is the recruitment of chaperones to the mitochondrial surface, whereas its ability to directly bind precursor proteins is largely dispensable. [ABSTRACT FROM AUTHOR]

The objective of gene set enrichment analysis (GSEA) in modern biological studies is to identify functional profiles in huge sets of biomolecules generated by high-throughput measurements of genes, transcripts, metabolites, and proteins. GSEA is based on a two-stage process using classical statistical analysis to score the input data and subsequent testing for overrepresentation of the enrichment score within a given functional coherent set. However, enrichment scores computed by different methods are merely statistically motivated and often elusive to direct biological interpretation. Here, we propose a novel approach, called Thermodynamically Motivated Enrichment Analysis (TMEA), to account for the energy investment in biological relevant processes. Therefore, TMEA is based on surprisal analysis, which offers a thermodynamic-free energy-based representation of the biological steady state and of the biological change. The contribution of each biomolecule underlying the changes in free energy is used in a Monte Carlo resampling procedure resulting in a functional characterization directly coupled to the thermodynamic characterization of biological responses to system perturbations. To illustrate the utility of our method on real experimental data, we benchmark our approach on plant acclimation to high light and compare the performance of TMEA with the most frequently used method for GSEA. [ABSTRACT FROM AUTHOR]