Do we want our data raw? Including binary mass spectrometry data in public proteomics data repositories

With the human Plasma Proteome Project (PPP) pilot phase completed, the largest and most ambitious proteomics experiment to date has reached its first milestone. The correspondingly impressive amount of data that came from this pilot project emphasized the need for a centralized dissemination mechanism and led to the development of a detailed, PPP specific data gathering infrastructure at the University of Michigan, Ann Arbor as well as the protein identifications database project at the European Bioinformatics Institute as a general proteomics data repository. One issue that crept up while discussing which data to store for the PPP concerns whether the raw, binary data coming from the mass spectrometers should be stored, or rather the more compact and already significantly processed peak lists. As this debate is not restricted to the PPP but relates to the proteomics community in general, we will attempt to detail the relative merits and caveats associated with centralized storage and dissemination of raw data and/or peak lists, building on the extensive experience gained during the PPP pilot phase. Finally, some suggestions are made for both immediate and future storage of MS data in public repositories.     

Who owns the data?

About ten years ago, a group of scientists began to argue that it was unfair to ask other scientists to pay to read the results of research that had been publicly funded.     

BioGPS and GXD: mouse gene expression data—the benefits and challenges of data integration

Mouse gene expression data are complex and voluminous. To maximize the utility of these data, they must be made readily accessible through databases, and those resources need to place the expression data in the larger biological context. Here we describe two community resources that approach these problems in different but complementary ways: BioGPS and the Mouse Gene Expression Database (GXD). BioGPS connects its large and homogeneous microarray gene expression reference data sets via plugins with a heterogeneous collection of external gene centric resources, thus casting a wide but loose net. GXD acquires different types of expression data from many sources and integrates these data tightly with other types of data in the Mouse Genome Informatics (MGI) resource, with a strong emphasis on consistency checks and manual curation. We describe and contrast the “loose” and “tight” data integration strategies employed by BioGPS and GXD, respectively, and discuss the challenges and benefits of data integration. BioGPS is freely available at http://biogps.org. GXD is freely available through the MGI web site (www.informatics.jax.org) or directly at www.informatics.jax.org/expression.shtml.     

Are all data types and connectivity models created equal? Validating common connectivity approaches with dispersal data

Aim

There is enormous interest in applying connectivity modelling to resistance surfaces for identifying corridors for conservation action. However, the multiple analytical approaches used to estimate resistance surfaces and predict connectivity across resistance surfaces have not been rigorously compared, and it is unclear what methods provide the best inferences about population connectivity. Using a large empirical data set on puma (Puma concolor), we are the first to compare several of the most common approaches for estimating resistance and modelling connectivity and validate them with dispersal data.

Location

Southern California, USA.

Methods

We estimate resistance using presence‐only data, GPS telemetry data from puma home ranges and genetic data using a variety of analytical methods. We model connectivity with cost distance and circuit theory algorithms. We then measure the ability of each data type and connectivity algorithm to capture GPS telemetry points of dispersing pumas.

Results

We found that resource selection functions based on GPS telemetry points and paths outperformed species distribution models when applied using cost distance connectivity algorithms. Point and path selection functions were not statistically different in their performance, but point selection functions were more sensitive to the transformation used to convert relative probability of use to resistance. Point and path selection functions and landscape genetics outperformed other methods when applied with cost distance; no methods outperformed one another with circuit theory.

Main conclusions

We conclude that path or point selection functions, or landscape genetic models, should be used to estimate landscape resistance for wildlife. In cases where resource limitations prohibit the collection of GPS collar or genetic data, our results suggest that species distribution models, while weaker, may still be sufficient for resistance estimation. We recommend the use of cost distance‐based approaches, such as least‐cost corridors and resistant kernels, for estimating connectivity and identifying functional corridors for terrestrial wildlife.

     

Can monitoring data contribute to the biodiversity-ecosystem function debate? Evaluating data from a highly dynamic ecosystem

One of the most controversially discussed topics in current biodiversity-ecosystem function research is the transfer of results from experimental and theoretical studies to natural ecosystems. At the same time, monitoring data on biodiversity are requested as key indicators for the state of an ecosystem in most environmental evaluation frameworks. We analyse two monitoring data sets comprising information on abundance and biomass of macrozoobenthos communities in the German Wadden Sea in order to evaluate how much information monitoring data on biodiversity provide concerning ecosystem functioning and what implications this information (or the lack thereof) has for future monitoring programmes. Our results show a positive correlation between number of species of macrozoobenthos and its standing stock. Despite differences in overall biomass and individual size in different functional groups, this correlation remained consistent for different feeding guilds and therefore is likely to be independent of certain species traits. Moreover, functional turnover analyses indicate that increasing species richness is needed to maintain biomass levels over increasing periods of time. Whereas our data thus corroborate predictions from theory, we could not determine any causal relationships, because monitoring data commonly include only vague proxies for very few functional parameters, in our case standing biomass as a proxy for production. As to the use of diversity as an indicator for ecosystem functioning, we advise that management decisions are to be based on verified causal relationships and therefore strongly suggest the general incorporation of unambiguous proxies for functional parameters in the measuring campaigns of monitoring programmes.     

Is DIA proteomics data FAIR? Current data sharing practices,available bioinformatics infrastructure and recommendations for the future

Data independent acquisition (DIA) proteomics techniques have matured enormously in recent years, thanks to multiple technical developments in, for example, instrumentation and data analysis approaches. However, there are many improvements that are still possible for DIA data in the area of the FAIR (Findability, Accessibility, Interoperability and Reusability) data principles. These include more tailored data sharing practices and open data standards since public databases and data standards for proteomics were mostly designed with DDA data in mind. Here we first describe the current state of the art in the context of FAIR data for proteomics in general, and for DIA approaches in particular. For improving the current situation for DIA data, we make the following recommendations for the future: (i) development of an open data standard for spectral libraries; (ii) make mandatory the availability of the spectral libraries used in DIA experiments in ProteomeXchange resources; (iii) improve the support for DIA data in the data standards developed by the Proteomics Standards Initiative; and (iv) improve the support for DIA datasets in ProteomeXchange resources, including more tailored metadata requirements.     

Maternal and environmental effects on offspring phenotypes in an oviparous lizard: do field data corroborate laboratory data?

A vast literature suggests that maternal factors and egg incubation conditions have substantial effects on offspring phenotypes in oviparous species. However, many studies that evaluate these effects have relied on experimental conditions that are rarely, if ever, encountered under natural conditions. To address this issue, we evaluated relationships among maternal factors, natural nest conditions, egg development in the field, and the resultant offspring phenotypes in a lizard with temperature-dependent sex determination, the jacky dragon (Amphibolurus muricatus, Agamidae). Many, but not all, of the relationships shown in our field-based study corroborate results from laboratory-based experiments. Offspring body size was affected primarily by egg size at oviposition, as well as by water uptake by eggs, rather than by environmental variables measured within the nest. Date of oviposition was related to offspring growth rate and body size prior to the onset of winter; this relationship is likely mediated through an influence on the timing of hatching. Nest temperature generated substantial variation in egg survival; nests that experienced higher temperatures and higher thermal fluctuations suffered relatively high egg mortality. Contrary to results from laboratory incubation, however, nest temperature did not predict offspring sex ratios. Hence, although many results from this field study corroborate those from the laboratory, caution is needed when extrapolating laboratory-incubation results to field conditions. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

New data on programmed aging — slow phenoptosis

This review summarizes the latest data on biochemistry and physiology of living organisms. These data suggest that aging, i.e. coordinated age-dependent weakening of many vital functions leading to gradual increase in the probability of dying, is not common to all organisms. Some species have been described whose probability of death does not depend on age or even decreases with age, this being accompanied by constant or increasing fertility. In the case of the naked mole rat (a non-aging mammal), a mechanism has been identified that protects this animal from cancer and the most common age-related diseases. The high molecular weight polysaccharide hyaluronan, a linear polymer composed of multiple repeated disaccharide of glucuronic acid and glucosamine, plays the key role in this mechanism. Hyaluronan is accumulated in the intercellular spaces in the organs and tissues of the naked mole rat. This polysaccharide provides early contact inhibition of cell division (anti-cancer effect). In addition, hyaluronan prevents the development of certain types of apoptosis, in particular, those induced by reactive oxygen species (ROS) (geroprotective effect preventing ROS-induced decrease in cellularity in the organs and tissues of aging organisms). Extraordinary longevity of the naked mole rat (over 30 years, which is long for a rodent the size of a mouse) is connected to its eusocial lifestyle, when only the “queen” and its few “husbands” breed, while the huge army of non-breeding “subordinates” provide the “royal family” with protection from predators, food, and construction and maintenance of an underground labyrinth size of a football field. This way of life removes the pressure of natural selection from the “family” and makes aging — the program that is counterproductive for the individual but increases “evolvability” of its offspring — unnecessary. The example of the naked mole rat demonstrates the optional character of the aging program for the organism. Many facts indicating that aging can be regulated by an organism provide another argument in favor of optionality of aging. Cases have been described when aging as a program useful for the evolution of offspring but counterproductive for the parental individual slows under conditions that threaten the very existence of the individual. These conditions include food restriction (the threat of death from starvation), heavy muscular work, decrease or increase in the environmental temperature, small amounts of poisons (including ROS; here we speak about the paradoxical geroprotective effect of the low doses of prooxidants that inhibit apoptosis). On the other hand, aging can be inhibited (and maybe even cancelled) artificially. This can be done by turning off the genes encoding the proteins participating in the aging program, such as FAT10, p66shc, and some others. In addition, the gene of the antioxidant enzyme catalase can be addressed into mitochondria, where it will split mitochondrial hydrogen peroxide, the level of which increases with age. However, today the simplest way to slow down the aging program is the use of mitochondria-targeted low molecular weight antioxidant compounds of plastoquinonyl decyltriphenylphosphonium-type (SkQ1), which prolong the life of animals, plants, and fungi and inhibit the development of many age-related diseases and symptoms.     

How reliable are experimental protein-protein interaction data?

Data of protein-protein interactions provide valuable insight into the molecular networks underlying a living cell. However, their accuracy is often questioned, calling for a rigorous assessment of their reliability. The computation offered here provides an intelligible mean to assess directly the rate of true positives in a data set of experimentally determined interacting protein pairs. We show that the reliability of high-throughput yeast two-hybrid assays is about 50%, and that the size of the yeast interactome is estimated to be 10,000-16,600 interactions.