Mitochondrial calcium handling is a particularly active research area in the neuroscience field, as it plays key roles in the regulation of several functions of the central nervous system, such as synaptic transmission and plasticity, astrocyte calcium signaling, neuronal activity{\ldots} In the last few decades, a panel of techniques have been developed to measure mitochondrial calcium dynamics, relying mostly on photonic microscopy, and including synthetic sensors, hybrid sensors and genetically encoded calcium sensors. The goal of this review is to endow the reader with a deep knowledge of the historical and latest tools to monitor mitochondrial calcium events in the brain, as well as a comprehensive overview of the current state of the art in brain mitochondrial calcium signaling. We will discuss the main calcium probes used in the field, their mitochondrial targeting strategies, their key properties and major drawbacks. In addition, we will detail the main roles of mitochondrial calcium handling in neuronal tissues through an extended report of the recent studies using mitochondrial targeted calcium sensors in neuronal and astroglial cells, in vitro and in vivo.
Mitochondrial genomes in the Pinaceae family are notable for their large size and structural complexity. In this study, we sequenced and analyzed the mitochondrial genome of Cathaya argyrophylla, an endangered and endemic Pinaceae species, uncovering a genome size of 18.99 Mb, meaning the largest mitochondrial genome reported to date. To investigate the mechanisms behind this exceptional size, we conducted comparative analyses with other Pinaceae species possessing both large and small mitochondrial genomes, as well as with other gymnosperms. We focused on repeat sequences, transposable element activity, RNA editing events, chloroplast-derived sequence transfers (mtpts), and sequence homology with nuclear genomes. Our findings indicate that while Cathaya argyrophylla and other extremely large Pinaceae mitochondrial genomes contain substantial amounts of repeat sequences and show increased activity of LINEs and LTR retrotransposons, these factors alone do not fully account for the genome expansion. Notably, we observed a significant incorporation of chloroplast-derived sequences in Cathaya argyrophylla and other large mitochondrial genomes, suggesting that extensive plastid-to-mitoc
Alpha satellite DNA is large tandem arrays of 150-400 bp units, and its origin remains an evolutionary mystery. In this research, we identified 1,545 alpha-satellite-like (SatL) repeat units in the nuclear genome of jewel wasp Nasonia vitripennis. Among them, thirty-nine copies of SatL were organized in two palindromic arrays in mitochondria, resulting in a 50% increase in the genome size. Strikingly, genomic neighborhood analyses of 1,516 nuclear SatL repeats revealed that they are located in NuMT (nuclear mitochondrial DNA) regions, and SatL phylogeny matched perfectly with mitochondrial genes and NuMT pseudogenes. These results support that SatL arrays originated from ten independent mitochondria insertion events into the nuclear genome within the last 500,000 years, after divergence from its sister species N. giraulti. Dramatic repeat GC-percent elevation (from 33.9% to 50.4%) is a hallmark of rapid SatL sequence evolution in mitochondria due to GC-biased gene conversion facilitated by the palindromic sequence pairing of the two mitochondrial SatL arrays. The nuclear SatL repeat arrays underwent substantial copy number expansion, from 12-15 (SatL1) to over 400 copies (SatL4). T
Promoters and enhancers are cis-regulatory elements (CREs), DNA sequences that bind transcription factor (TF) proteins to up- or down-regulate target genes. Decades-long efforts yielded TF-DNA interaction models that predict how strongly an individual TF binds arbitrary DNA sequences and how individual binding events on the CRE combine to affect gene expression. These insights can be synthesized into a global, biophysically-realistic, and quantitative genotype-phenotype (GP) map for gene regulation, a "holy grail" for the application of evolutionary theory. A global map provides a rare opportunity to simulate long-term evolution of regulatory sequences and pose several fundamental questions: How long does it take to evolve CREs de novo? How many non-trivial regulatory functions exist in sequence space? How connected are they? For which regulatory architecture is CRE evolution most rapid and evolvable? In this article, the second of a two-part series, we review the application of evolutionary concepts - epistasis, robustness, evolvability, tunability, plasticity, and bet-hedging - to the evolution of gene regulatory sequences. We then evaluate the potential for a unifying theory for
Promoters and enhancers are cis-regulatory elements (CREs), DNA sequences that bind transcription factor (TF) proteins to up- or down-regulate target genes. Decades-long efforts yielded TF-DNA interaction models that predict how strongly an individual TF binds arbitrary DNA sequences and how individual binding events on the CRE combine to affect gene expression. These insights can be synthesized into a global, biophysically-realistic, and quantitative genotype-phenotype (GP) map for gene regulation, a "holy grail" for the application of evolutionary theory. A global map provides a rare opportunity to simulate long-term evolution of regulatory sequences and pose several fundamental questions: How long does it take to evolve CREs de novo? How many non-trivial regulatory functions exist in sequence space? How connected are they? For which regulatory architecture is CRE evolution most rapid and evolvable? In this article, the first of a two-part series, we briefly review the pertinent modeling and simulation efforts for a unique system that enables close, quantitative, and mechanistic links between biophysics, as well as systems, synthetic, and evolutionary biology.
The proper functioning of mitochondria requires that both the mitochondrial and the nuclear genome are functional. To investigate the importance of the mitochondrial genome, which encodes only 13 subunits of the respiratory complexes, the mitochondrial rRNAs and a few tRNAs, we performed a comparative study on the 143B cell line and on its Rho-0 counterpart, i.e., devoid of mitochondrial DNA. Quantitative differences were found, of course in the respiratory complexes subunits, but also in the mitochondrial translation apparatus, mainly mitochondrial ribosomal proteins, and in the ion and protein import system, i.e., including membrane proteins. Various mitochondrial metabolic processes were also altered, especially electron transfer proteins and some dehydrogenases, but quite often on a few proteins for each pathway. This study also showed variations in some hypothetical or poorly characterized proteins, suggesting a mitochondrial localization for these proteins. Examples include a stomatin-like protein and a protein sharing homologies with bacterial proteins implicated in tyrosine catabolism. Proteins involved in apoptosis control are also found modulated in Rho-0 mitochondria.
Target tracking entails the estimation of the evolution of the target state over time, namely the target trajectory. Different from the classical state space model, our series of studies, including this paper, model the collection of the target state as a stochastic process (SP) that is further decomposed into a deterministic part which represents the trend of the trajectory and a residual SP representing the residual fitting error. Subsequently, the tracking problem is formulated as a learning problem regarding the trajectory SP for which a key part is to estimate a trajectory FoT (T-FoT) best fitting the measurements in time series. For this purpose, we consider the polynomial T-FoT and address the regularized polynomial T-FoT optimization employing two distinct regularization strategies seeking trade-off between the accuracy and simplicity. One limits the order of the polynomial and then the best choice is determined by grid searching in a narrow, bounded range while the other adopts $\ell_0$ norm regularization for which the hybrid Newton solver is employed. Simulation results obtained in both single and multiple maneuvering target scenarios demonstrate the effectiveness of our
Mitochondrial diseases are largely caused by dysfunction in mitochondrial proteins. However, annotations of human mitochondrial proteins are scattered across various public databases and individual studies. To facilitate research aimed at elucidating mitochondrial functions, we constructed the MEGADOCK-Web-Mito database as a protein-protein interaction (PPI) prediction data archive, including prediction results for exhaustive protein pairs of 654 mitochondria-related human proteins. MEGADOCK-Web-Mito enables users to search for all PPI prediction results efficiently and comprehensively. In particular, we linked functional annotations to each human mitochondrial protein. The comprehensive and specialized human mitochondrial PPI prediction results and searching function of MEGADOCK-Web-Mito will support further research on mitochondria and mitochondrial diseases.
Rank--frequency distributions of nucleotide sequences in mitochondrial DNA are defined in a way analogous to the linguistic approach, with the highest-frequent nucleobase serving as a whitespace. For such sequences, entropy and mean length are calculated. These parameters are shown to discriminate the species of the <I>Felidae</I> (cats) and <I>Ursidae</I> (bears) families. From purely numerical values we are able to see in particular that giant pandas are bears while koalas are not. The observed linear relation between the parameters is explained using a simple probabilistic model. The approach based on the nonadditive generalization of the Bose-distribution is used to analyze the frequency spectra of the nucleotide sequences. In this case, the separation of families is not very sharp. Nevertheless, the distributions for <I>Felidae</I> have on average longer tails comparing to <I>Ursidae</I>.
Supervised models for Word Sense Disambiguation (WSD) currently yield to state-of-the-art results in the most popular benchmarks. Despite the recent introduction of Word Embeddings and Recurrent Neural Networks to design powerful context-related features, the interest in improving WSD models using Semantic Lexical Resources (SLRs) is mostly restricted to knowledge-based approaches. In this paper, we enhance "modern" supervised WSD models exploiting two popular SLRs: WordNet and WordNet Domains. We propose an effective way to introduce semantic features into the classifiers, and we consider using the SLR structure to augment the training data. We study the effect of different types of semantic features, investigating their interaction with local contexts encoded by means of mixtures of Word Embeddings or Recurrent Neural Networks, and we extend the proposed model into a novel multi-layer architecture for WSD. A detailed experimental comparison in the recent Unified Evaluation Framework (Raganato et al., 2017) shows that the proposed approach leads to supervised models that compare favourably with the state-of-the art.
Mitochondrial networks exhibit a variety of complex behaviors, including coordinated cell-wide oscillations of energy states as well as a phase transition (depolarization) in response to oxidative stress. Since functional and structural properties are often interwinded, here we characterize the structure of mitochondrial networks in mouse embryonic fibroblasts using network tools and percolation theory. Subsequently we perturbed the system either by promoting the fusion of mitochondrial segments or by inducing mitochondrial fission. Quantitative analysis of mitochondrial clusters revealed that the structural parameters of healthy mitochondria lay in between the extremes of highly fragmented and completely fusioned networks. We confirmed our results by contrasting our emprirical findings with the predictions of a recently described computational model of mitochondrial network emergence based on fission-fusion kinetics. Altogether these results not only offer an objective methodology to parametrize the complexity of this organelle but add weight to the idea that mitochondrial networks behave as critical systems and undergo structural phase transitions.
Living organisms continuously harness energy to perform complex functions for their adaptation and survival while part of that energy is dissipated in the form of heat or chemical waste. Determining the energetic cost and the efficiency of specific cellular processes remains a largely open problem. Here, we analyze the efficiency of mitochondrial adenosine triphosphate (ATP) production through the tricarboxylic acid (TCA) cycle and oxidative phosphorylation that generates most of the cellular chemical energy in eukaryotes. The regulation of this pathway by calcium signaling represents a well-characterized example of a regulatory cross-talk that can affect the energetic output of a metabolic pathway, but its concrete energetic impact remains elusive. On the one hand, calcium enhances ATP production by activating key enzymes of the TCA cycle, but on the other hand calcium homeostasis depends on ATP availability. To evaluate how calcium signaling impacts the efficiency of mitochondrial metabolism, we propose a detailed kinetic model describing the calcium-mitochondria cross-talk and we analyze it using a nonequilibrium thermodynamic approach: after identifying the effective reactions
Cell-to-cell heterogeneity drives a range of (patho)physiologically important phenomena, such as cell fate and chemotherapeutic resistance. The role of metabolism, and particularly mitochondria, is increasingly being recognised as an important explanatory factor in cell-to-cell heterogeneity. Most eukaryotic cells possess a population of mitochondria, in the sense that mitochondrial DNA (mtDNA) is held in multiple copies per cell, where the sequence of each molecule can vary. Hence intra-cellular mitochondrial heterogeneity is possible, which can induce inter-cellular mitochondrial heterogeneity, and may drive aspects of cellular noise. In this review, we discuss sources of mitochondrial heterogeneity (variations between mitochondria in the same cell, and mitochondrial variations between supposedly identical cells) from both genetic and non-genetic perspectives, and mitochondrial genotype-phenotype links. We discuss the apparent homeostasis of mtDNA copy number, the observation of pervasive intra-cellular mtDNA mutation (we term `microheteroplasmy') and developments in the understanding of inter-cellular mtDNA mutation (`macroheteroplasmy'). We point to the relationship between mit
Variations in mitochondrial genes are usually considered to infer phylogenies. However some of these genes are lesser constraint than other ones, and thus may blur the phylogenetic signals shared by the majority of the mitochondrial DNA sequences. To investigate such effects, in this research work, the molecular phylogeny of the genus Taenia is studied using 14 coding sequences extracted from mitochondrial genomes of 17 species. We constructed 16,384 trees, using a combination of 1 up to 14 genes. We obtained 131 topologies, and we showed that only four particular instances were relevant. Using further statistical investigations, we then extracted a particular topology, which displays more robustness properties.
Mitochondrial DNA (mtDNA) mutations cause severe congenital diseases but may also be associated with healthy aging. MtDNA is stochastically replicated and degraded, and exists within organelles which undergo dynamic fusion and fission. The role of the resulting mitochondrial networks in the time evolution of the cellular proportion of mutated mtDNA molecules (heteroplasmy), and cell-to-cell variability in heteroplasmy (heteroplasmy variance), remains incompletely understood. Heteroplasmy variance is particularly important since it modulates the number of pathological cells in a tissue. Here, we provide the first wide-reaching theoretical framework which bridges mitochondrial network and genetic states. We show that, under a range of conditions, the (genetic) rate of increase in heteroplasmy variance and de novo mutation are proportionally modulated by the (physical) fraction of unfused mitochondria, independently of the absolute fission-fusion rate. In the context of selective fusion, we show that intermediate fusion/fission ratios are optimal for the clearance of mtDNA mutants. Our findings imply that modulating network state, mitophagy rate and copy number to slow down heteroplas
Metabolic pathways describe chains of enzymatic reactions. Their modelling is a key point to understand living systems. An enzymatic reaction is an interaction between one or several metabolites (substrates) and an enzyme (simple protein or enzymatic complex build of several subunits). In our Mitochondria in Silico Project, MitoScop, we study the metabolism of the mitochondria, an intra-cellular organelle. Many ordinary differential equation models are available in the literature. They well fit experimental results on flux values inside the metabolic pathways, but many parameters are di$\pm$cult to transcribe with such models: localization of enzymes, rules about the reactions scheduler, etc Moreover, a model of a significant part of mitochondrial metabolism could become very complex and contain more than 50 equations. In this context, the multi-agents systems appear as an alternative to model the metabolic pathways. Firstly, we have looked after membrane design. The mitochondria is a particular case because the inner mitochondrial space, ie matricial space, is delimited by two membranes: the inner and the outer one. In addition to matricial enzymes, other enzymes are located insid
Muscle uses Ca2+ as a messenger to control contraction and relies on ATP to maintain the intracellular Ca2+ homeostasis. Mitochondria are the major sub-cellular organelle of ATP production. With a negative inner membrane potential, mitochondria take up Ca2+ from their surroundings, a process called mitochondrial Ca2+ uptake. Under physiological conditions, Ca2+ uptake into mitochondria promotes ATP production. Excessive uptake causes mitochondrial Ca2+ overload, which activates downstream adverse responses leading to cell dysfunction. Moreover, mitochondrial Ca2+ uptake could shape spatio-temporal patterns of intracellular Ca2+ signaling. Malfunction of mitochondrial Ca2+ uptake is implicated in muscle degeneration. Unlike non-excitable cells, mitochondria in muscle cells experience dramatic changes of intracellular Ca2+ levels. Besides the sudden elevation of Ca2+ level induced by action potentials, Ca2+ transients in muscle cells can be as short as a few milliseconds during a single twitch or as long as minutes during tetanic contraction, which raises the question whether mitochondrial Ca2+ uptake is fast and big enough to shape intracellular Ca2+ signaling during excitation-cont
DNA constructs and their annotated sequence maps have been rapidly accumulating with the advancement of DNA cloning, synthesis, and assembly methods. Such a resource has the potential to be optimally utilized in an autonomous DNA building platform. However, most DNA design processes today remain manually operated with the assistance of graphical user interface (GUI) software. Furthermore, as seen commonly in the life sciences, reproducibility of DNA construction process descriptions is usually not guaranteed, and utilization of previously developed materials and protocols is not appropriately credited. Here, we developed an open-source process description and resource sharing framework QUEEN (a framework to generate quinable and efficiently editable nucleotide sequence resources) to resolve these issues in building DNA. QUEEN enables the flexible design of new DNA by using existing DNA resource files and recoding the construction process in an output file (GenBank file format). The GenBank files generated by QUEEN are able to regenerate the process codes that perfectly clone themselves and bequeath the design history to successive DNA constructs that recycle their partial resources
This paper presents a comprehensive survey of corpora and lexical resources available for Turkish. We review a broad range of resources, focusing on the ones that are publicly available. In addition to providing information about the available linguistic resources, we present a set of recommendations, and identify gaps in the data available for conducting research and building applications in Turkish Linguistics and Natural Language Processing.
Mitochondria are complex organelles, and their proteomics analysis requires a combination of techniques. The emphasis in this chapter is made first on mitochondria preparation from cultured mammalian cells, then on the separation of the mitochondrial proteins with two-dimensional electrophoresis (2DE), showing some adjustment over the classical techniques to improve resolution of the mitochondrial proteins. This covers both the protein solubilization, the electrophoretic part per se, and the protein detection on the gels, which makes the interface with the protein identification part relying on mass spectrometry.