Proteomics to go: Proteomatic enables the user-friendly creation of versatile MS/MS data evaluation workflows

We present Proteomatic, an operating system independent and user-friendly platform that enables the construction and execution of MS/MS data evaluation pipelines using free and commercial software. Required external programs such as for peptide identification are downloaded automatically in the case of free software. Due to a strict separation of functionality and presentation, and support for multiple scripting languages, new processing steps can be added easily

CropSight: A scalable and open-source information management system for distributed plant phenotyping and IoT-based crop management

Background: High-quality plant phenotyping and climate data lay the foundation of phenotypic analysis and genotype-environment interaction, providing important evidence not only for plant scientists to understand the dynamics between crop performance, genotypes, and environmental factors, but also for agronomists and farmers to closely monitor crops in fluctuating agricultural conditions. With the rise of Internet of Things technologies (IoT) in recent years, many IoT-based remote sensing devices have been applied to plant phenotyping and crop monitoring, which are generating terabytes of biological datasets every day. However, it is still technically challenging to calibrate, annotate, and aggregate the big data effectively, especially when they were produced in multiple locations, at different scales. Findings: CropSight is a PHP and SQL based server platform, which provides automated data collation, storage, and information management through distributed IoT sensors and phenotyping workstations. It provides a two-component solution to monitor biological experiments through networked sensing devices, with interfaces specifically designed for distributed plant phenotyping and centralised data management. Data transfer and annotation are accomplished automatically though an HTTP accessible RESTful API installed on both device-side and server-side of the CropSight system, which synchronise daily representative crop growth images for visual-based crop assessment and hourly microclimate readings for GxE studies. CropSight also supports the comparison of historical and ongoing crop performance whilst different experiments are being conducted. Conclusions: As a scalable and open-source information management system, CropSight can be used to maintain and collate important crop performance and microclimate datasets captured by IoT sensors and distributed phenotyping installations. It provides near real-time environmental and crop growth monitoring in addition to historical and current experiment comparison through an integrated cloud-ready server system. Accessible both locally in the field through smart devices and remotely in an office using a personal computer, CropSight has been applied to field experiments of bread wheat prebreeding since 2016 and speed breeding since 2017. We believe that the CropSight system could have a significant impact on scalable plant phenotyping and IoT-style crop management to enable smart agricultural practices in the near future

What is cost-efficient phenotyping? Optimizing costs for different scenarios

Progress in remote sensing and robotic technologies decreases the hardware costs of phenotyping. Here, we first review cost-effective imaging devices and environmental sensors, and present a trade-off between investment and manpower costs. We then discuss the structure of costs in various real-world scenarios. Hand-held low-cost sensors are suitable for quick and infrequent plant diagnostic measurements. In experiments for genetic or agronomic analyses, (i) major costs arise from plant handling and manpower; (ii) the total costs per plant/microplot are similar in robotized platform or field experiments with drones, hand-held or robotized ground vehicles; (iii) the cost of vehicles carrying sensors represents only 5–26% of the total costs. These conclusions depend on the context, in particular for labor cost, the quantitative demand of phenotyping and the number of days available for phenotypic measurements due to climatic constraints. Data analysis represents 10–20% of total cost if pipelines have already been developed. A trade-off exists between the initial high cost of pipeline development and labor cost of manual operations. Overall, depending on the context and objsectives, “cost-effective” phenotyping may involve either low investment (“affordable phenotyping”), or initial high investments in sensors, vehicles and pipelines that result in higher quality and lower operational costs

Overexpression of the Rieske FeS protein of the Cytochrome b 6 f complex increases C4 photosynthesis in Setaria viridis.

C4 photosynthesis is characterised by a CO2 concentrating mechanism that operates between mesophyll and bundle sheath cells increasing CO2 partial pressure at the site of Rubisco and photosynthetic efficiency. Electron transport chains in both cell types supply ATP and NADPH for C4 photosynthesis. Cytochrome b 6 f is a key control point of electron transport in C3 plants. To study whether C4 photosynthesis is limited by electron transport we constitutively overexpressed the Rieske FeS subunit in Setaria viridis. This resulted in a higher Cytochrome b 6 f content in mesophyll and bundle sheath cells without marked changes in the abundances of other photosynthetic proteins. Rieske overexpression plants showed better light conversion efficiency in both Photosystems and could generate higher proton-motive force across the thylakoid membrane underpinning an increase in CO2 assimilation rate at ambient and saturating CO2 and high light. Our results demonstrate that removing electron transport limitations can increase C4 photosynthesis

Association of Ferredoxin:NADP+ oxidoreductase with the photosynthetic apparatus modulates electron transfer in Chlamydomonas reinhardtii

R.M. acknowledges support from the MEXT (Ministry of Education, Culture, Sports, Science and Technology, 15K21122). T.H. gratefully acknowledges support from the DFG (DIP project cooperation “Nanoengineered optoelectronics with biomaterials and bioinspired assemblies”) and the Volkswagen Foundation (LigH2t). G.K. acknowledges support from CREST, Japan Science and Technology Agency. M.H. acknowledges support from the DFG (Deutsche Forschungsgemeinschaft, HI 739/13-1)

Measuring the dynamic photosynthome

Background: Photosynthesis underpins plant productivity and yet is notoriously sensitive to small changes inenvironmental conditions, meaning that quantitation in nature across different time scales is not straightforward. The ‘dynamic’ changes in photosynthesis (i.e. the kinetics of the various reactions of photosynthesis in response to environmental shifts) are now known to be important in driving crop yield. Scope: It is known that photosynthesis does not respond in a timely manner, and even a small temporal “mismatch” between a change in the environment and the appropriate response of photosynthesis toward optimality can result in a fall in productivity. Yet the most commonly measured parameters are still made at steady state or a temporary steady state (including those for crop breeding purposes), meaning that new photosynthetic traits remain undiscovered. Conclusions: There is a great need to understand photosynthesis dynamics from a mechanistic and biological viewpoint especially when applied to the field of ‘phenomics’ which typically uses large genetically diverse populations of plants. Despite huge advances in measurement technology in recent years, it is still unclear whether we possess the capability of capturing and describing the physiologically relevant dynamic features of field photosynthesis in sufficient detail. Such traits are highly complex, hence we dub this the ‘photosynthome’. This review sets out the state of play and describes some approaches that could be made to address this challenge with reference to the relevant biological processes involved

2DB: a Proteomics database for storage, analysis, presentation, and retrieval of information from mass spectrometric experiments

<p>Abstract</p> <p>Background</p> <p>The amount of information stemming from proteomics experiments involving (multi dimensional) separation techniques, mass spectrometric analysis, and computational analysis is ever-increasing. Data from such an experimental workflow needs to be captured, related and analyzed. Biological experiments within this scope produce heterogenic data ranging from pictures of one or two-dimensional protein maps and spectra recorded by tandem mass spectrometry to text-based identifications made by algorithms which analyze these spectra. Additionally, peptide and corresponding protein information needs to be displayed.</p> <p>Results</p> <p>In order to handle the large amount of data from computational processing of mass spectrometric experiments, automatic import scripts are available and the necessity for manual input to the database has been minimized. Information is in a generic format which abstracts from specific software tools typically used in such an experimental workflow. The software is therefore capable of storing and cross analysing results from many algorithms. A novel feature and a focus of this database is to facilitate protein identification by using peptides identified from mass spectrometry and link this information directly to respective protein maps. Additionally, our application employs spectral counting for quantitative presentation of the data. All information can be linked to hot spots on images to place the results into an experimental context. A summary of identified proteins, containing all relevant information per hot spot, is automatically generated, usually upon either a change in the underlying protein models or due to newly imported identifications. The supporting information for this report can be accessed in multiple ways using the user interface provided by the application.</p> <p>Conclusion</p> <p>We present a proteomics database which aims to greatly reduce evaluation time of results from mass spectrometric experiments and enhance result quality by allowing consistent data handling. Import functionality, automatic protein detection, and summary creation act together to facilitate data analysis. In addition, supporting information for these findings is readily accessible via the graphical user interface provided. The database schema and the implementation, which can easily be installed on virtually any server, can be downloaded in the form of a compressed file from our project webpage.</p

Residues PsaB Asp612 and PsaB Glu613 of Photosystem I Confer pH-Dependent Binding of Plastocyanin and Cytochrome <i>c</i>₆

The binding and electron transfer between plastocyanin (pc) or cytochrome <i>c</i>₆ (cyt c₆) and photosystem I (PSI) can be described by hydrophobic as well as electrostatic interactions. The two α helices, <i>l</i> and <i>l</i>′ in PsaB and PsaA, respectively, are involved in forming the hydrophobic interaction site at the oxidizing site of PSI. To obtain mechanistic insights into the function of the two negatively charged residues D612 and E613, present in α helix <i>l</i> of PsaB, we exchanged both residues by site-directed mutagenesis with His and transformed a PsaB deficient mutant of <i>Chlamydomonas reinhardtii</i>. Flash-induced absorption spectroscopy revealed that PSI harboring the changes D612H and E613H had a high affinity toward binding of the electron donors and possessed an altered pH dependence of electron transfer with pc and cyt c₆. Despite optimized binding and electron transfer between the altered PSI and its electron donors, the mutant strain PsaB-D612H/E613H exhibited a strong light sensitive growth phenotype, indicating that decelerated turnover between pc/cyt c₆ and PSI with respect to electron transfer is deleterious to the cells