We analyzed an ex vivo model of in situ aged human dermal fibroblasts, obtained from 15 adult healthy donors from three different age groups using an unbiased quantitative proteome-wide approach applying label-free mass spectrometry. Thereby, we identified 2409 proteins, including 43 proteins with an age-associated abundance change. Most of the differentially abundant proteins have not been described in the context of fibroblasts’ aging before, but the deduced biological processes confirmed known hallmarks of aging and led to a consistent picture of eight biological categories involved in fibroblast aging, namely proteostasis, cell cycle and proliferation, development and differentiation, cell death, cell organization and cytoskeleton, response to stress, cell communication and signal transduction, as well as RNA metabolism and translation. The exhaustive analysis of protein and mRNA data revealed that 77% of the age-associated proteins were not linked to expression changes of the corresponding transcripts. This is in line with an associated miRNA study and led us to the conclusion that most of the age-associated alterations detected at the proteome level are likely caused post-transcriptionally rather than by differential gene expression. In summary, our findings led to the characterization of novel proteins potentially associated with fibroblast aging and revealed that primary cultures of in situ aged fibroblasts are characterized by moderate age-related proteomic changes comprising the multifactorial process of aging.
Shallow marine ecosystems naturally experience fluctuating physicochemical conditions across spatial and temporal scales. Widespread coral-bleaching events, induced by prolonged heat stress, highlight the importance of how the duration and frequency of thermal stress influence the adaptive physiology of photosymbiotic calcifiers. Large benthic foraminifera harboring algal endosymbionts are major tropical carbonate producers and bioindicators of ecosystem health. Like corals, they are sensitive to thermal stress and bleach at temperatures temporarily occurring in their natural habitat and projected to happen more frequently. However, their thermal tolerance has been studied so far only by chronic exposure, so how they respond under more realistic episodic heat-event scenarios remains unknown. Here, we determined the physiological responses of Amphistegina gibbosa, an abundant western Atlantic foraminifera, to four different treatments––control, single, episodic, and chronic exposure to the same thermal stress (32°C)––in controlled laboratory cultures. Exposure to chronic thermal stress reduced motility and growth, while antioxidant capacity was elevated, and photosymbiont variables (coloration, oxygen-production rates, chlorophyll a concentration) indicated extensive bleaching. In contrast, single- and episodic-stress treatments were associated with higher motility and growth, while photosymbiont variables remained stable. The effects of single and episodic heat events were similar, except for the presumable occurrence of reproduction, which seemed to be suppressed by both episodic and chronic stress. The otherwise different responses between treatments with thermal fluctuations and chronic stress indicate adaptation to thermal peaks, but not to chronic exposure expected to ensue when baseline temperatures are elevated by climate change. This firstly implies that marine habitats with a history of fluctuating thermal stress potentially support resilient physiological mechanisms among photosymbiotic organisms. Secondly, there seem to be temporal constraints related to heat events among coral reef environments and reinforces the importance of temporal fluctuations in stress exposure in global-change studies and projections.
BackgroundThe classification of samples on a molecular level has manifold applications, from patient classification regarding cancer treatment to phylogenetics for identifying evolutionary relationships between species. Modern methods employ the alignment of DNA or amino acid sequences, mostly not genome-wide but only on selected parts of the genome. Recently proteomics-based approaches have become popular. An established method for the identification of peptides and proteins is liquid chromatography-tandem mass spectrometry (LC-MS/MS). First, protein sequences from MS/MS spectra are identified by means of database searches, given samples with known genome-wide sequence information, then sequence based methods are applied. Alternatively, de novo peptide sequencing algorithms annotate MS/MS spectra and deduce peptide/protein information without a database. A newer approach independent of additional information is to directly compare unidentified tandem mass spectra. The challenge then is to compute the distance between pairwise MS/MS runs consisting of thousands of spectra.MethodsWe present DISMS2, a new algorithm to calculate proteome-wide distances directly from MS/MS data, extending the algorithm compareMS2, an approach that also uses a spectral comparison pipeline.ResultsOur new more flexible algorithm, DISMS2, allows for the choice of the spectrum distance measure and includes different spectra preprocessing and filtering steps that can be tailored to specific situations by parameter optimization.ConclusionsDISMS2 performs well for samples from species with and without database annotation and thus has clear advantages over methods that are purely based on database search.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1514-2) contains supplementary material, which is available to authorized users.
In proteomics, liquid chromatography-tandem mass spectrometry (LC-MS/MS) is established for identifying peptides and proteins. Duplicated spectra, that is, multiple spectra of the same peptide, occur both in single MS/MS runs and in large spectral libraries. Clustering tandem mass spectra is used to find consensus spectra, with manifold applications. First, it speeds up database searches, as performed for instance by Mascot. Second, it helps to identify novel peptides across species. Third, it is used for quality control to detect wrongly annotated spectra. We compare different clustering algorithms based on the cosine distance between spectra. CAST, MS-Cluster, and PRIDE Cluster are popular algorithms to cluster tandem mass spectra. We add well-known algorithms for large data sets, hierarchical clustering, DBSCAN, and connected components of a graph, as well as the new method N-Cluster. All algorithms are evaluated on real data with varied parameter settings. Cluster results are compared with each other and with peptide annotations based on validation measures such as purity. Quality control, regarding the detection of wrongly (un)annotated spectra, is discussed for exemplary resulting clusters. N-Cluster proves to be highly competitive. All clustering results benefit from the so-called DISMS2 filter that integrates additional information, for example, on precursor mass.
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