A new method to detect event-related potentials based on Pearson’s correlation

Event-related potentials (ERPs) are widely used in brain-computer interface applications and in neuroscience.  Normal EEG activity is rich in background noise, and therefore, in order to detect ERPs, it is usually necessary to take the average from multiple trials to reduce the effects of this noise.  The noise produced by EEG activity itself is not correlated with the ERP waveform and so, by calculating the average, the noise is decreased by a factor inversely proportional to the square root of N, where N is the number of averaged epochs. This is the easiest strategy currently used to detect ERPs, which is based on calculating the average of all ERP’s waveform, these waveforms being time- and phase-locked.  In this paper, a new method called GW6 is proposed, which calculates the ERP using a mathematical method based only on Pearson’s correlation. The result is a graph with the same time resolution as the classical ERP and which shows only positive peaks representing the increase—in consonance with the stimuli—in EEG signal correlation over all channels.  This new method is also useful for selectively identifying and highlighting some hidden components of the ERP response that are not phase-locked, and that are usually hidden in the standard and simple method based on the averaging of all the epochs.  These hidden components seem to be caused by variations (between each successive stimulus) of the ERP’s inherent phase latency period (jitter), although the same stimulus across all EEG channels produces a reasonably constant phase. For this reason, this new method could be very helpful to investigate these hidden components of the ERP response and to develop applications for scientific and medical purposes. Moreover, this new method is more resistant to EEG artifacts than the standard calculations of the average and could be very useful in research and neurology.  The method we are proposing can be directly used in the form of a process written in the well-known Matlab programming language and can be easily and quickly written in any other software language.     

A Beginner’s Guide to Phylogenetics

Metagenomics and the development of high throughput next generation sequencing capabilities have forced significant development in the field of phylogenetics: the study of the evolutionary relatedness of the planet’s inhabitants. Herein, I review the major tree-building strategies, challenges and opportunities which exist in this rapidly expanding field of evolutionary biology.     

Application of the ‘profiles of relationship’ method to distantly related proteins

Summary An analysis is made of the applicability of the recently published profiles of relationship method for establishing evolutionary relatedness among proteins by using the distantly related proinsulin and neurotoxin protein se-quences as a test object. The method is based on a simultaneous group analysis of both the frequency of acceptance of mutations and their genetic code inter-changeability. Regularities in the patterns of the profiles, which reflect decreased similarity with the passage of time, are established for typical cases of closely related, distantly related and unrelated proteins. This makes it possible to distinguish distantly related from unrelated proteins without extensive statistical randomization procedures. New evidence is stated in favour of a previously suggested definition of interchangeability which does not consider the third base in the codon. The applicability of the profiles of relationship method is examined on the distant relationship between proinsulin and the snake and scorpion neurotoxins which has been established previously by means of conventional approaches.     

A multi-scale approach to identify invasion drivers and invaders’ future dynamics

Climate, land use and disturbances are well known drivers of invasion. However, their relative influence may change across spatial scales, where climate is expected to be the main filter at broad scales; land use is expected to have more influence at intermediate scales, and disturbance, at fine ones. Understanding the underlying processes that drive invasion patterns at different spatial scales is thus crucial to be able to anticipate the future spread of invaders. Here, we quantified the relative importance of climate, land use, and disturbance on the distribution of the invasive trees Ailanthus altissima and Robinia pseudoacacia, across three nested spatial scales, namely global, country (Spain) and riverbank (three riparian riverbanks). To do so, for each species and scale, we built ensemble species distribution models. We also identified their range filling and inferred the most suitable areas in Spain for them to spread. In general, our study confirms that climate acts as an initial coarse filter of species distribution, whilst both climate and land use were important at the country scale; at the riverbank scale human-mediated disturbances gained importance. However, R. pseudoacacia and A. altissima showed differences in their degree of range filling, where A. altissima has a higher potential for range expansion in the near future. Overall, the integration of different scales into invasion studies shows a great potential to enrich our understanding of species-habitat relationships, and to help anticipate their future dynamics.     

A robust method to estimate the largest Lyapunov exponent of noisy signals: A revision to the Rosenstein’s algorithm

This study proposed a revision to the Rosenstein’s method of numerical calculation of the largest Lyapunov exponent (LyE) to make it more robust to noise. To this aim, the effect of increasing number of initial neighboring points on the LyE value was investigated and compared to values obtained by filtering the time series. Both simulated (Lorenz and passive dynamic walker) and experimental (human walking) time series were used to calculate the LyE. The number of initial neighbors used to calculate LyE for all time series was 1 (the original Rosenstein’s method), 2, 3, 4, 5, 10, 15, 20, 25, and 30 data points. The results demonstrated that the LyE graph reached a plateau at the 15-point neighboring condition implying that the LyE values calculated using at least 15 neighboring points were consistent. The proposed method could be used to calculate more consistent LyE values in experimental time series acquired from biological systems where noise is omnipresent.     

A rapid and sensitive high-throughput screening method to identify compounds targeting protein–nucleic acids interactions

DNA-binding and RNA-binding proteins are usually considered ‘undruggable’ partly due to the lack of an efficient method to identify inhibitors from existing small molecule repositories. Here we report a rapid and sensitive high-throughput screening approach to identify compounds targeting protein–nucleic acids interactions based on protein–DNA or protein–RNA interaction enzyme-linked immunosorbent assays (PDI-ELISA or PRI-ELISA). We validated the PDI-ELISA method using the mammalian high-mobility-group protein AT-hook 2 (HMGA2) as the protein of interest and netropsin as the inhibitor of HMGA2–DNA interactions. With this method we successfully identified several inhibitors and an activator for HMGA2–DNA interactions from a collection of 29 DNA-binding compounds. Guided by this screening excise, we showed that netropsin, the specific inhibitor of HMGA2–DNA interactions, strongly inhibited the differentiation of the mouse pre-adipocyte 3T3-L1 cells into adipocytes, most likely through a mechanism by which the inhibition is through preventing the binding of HMGA2 to the target DNA sequences. This method should be broadly applicable to identify compounds or proteins modulating many DNA-binding or RNA-binding proteins.     

Breaking down to build up: Neuroligin’s C-terminal domain strengthens the synapse

The mechanisms by which neuroligin adhesion molecules modulate synaptic plasticity remain unclear. In this issue, Liu et al. (2016. J. Cell Biol. http://dx.doi.org/10.1083/jcb.201509023) demonstrate that neuroligin 1 promotes actin assembly associated with synaptic strengthening independent of adhesion, suggesting additional ways for neuroligins to contribute to neuronal development and disease pathology.Spines are actin-enriched dendritic protrusions that serve as the major site of excitatory neurotransmission, underlying learning and memory formation (Lynch et al., 2007). Spines associate with presynaptic axon terminals through diverse adhesion molecules to form synapses (Siddiqui and Craig, 2011). Dynamic rearrangements of these synaptic adhesions and of the underlying actin cytoskeleton lead to either strengthening or weakening of particular synaptic connections. Synaptic strengthening, or long-term potentiation (LTP), is initiated by excitation of glutamate N-methyl-d-aspartate (NMDA) receptors, which promotes cleavage of synaptic adhesion molecules and disassembly of actin filaments (Lynch et al., 2007). Actin disassembly is mediated in part by recruitment of the actin-severing protein cofilin into the spine (Bosch et al., 2014). After the breakdown of the existing synaptic architecture, the actin cytoskeleton is stabilized again via Rac1-driven actin polymerization (Rex et al., 2009) and phosphorylation-mediated cofilin inactivation (Bosch et al., 2014). In parallel, recruitment and anchoring of synaptic adhesion molecules, including neuroligin 1 (NLG1; Schapitz et al., 2010) and glutamate receptors, increases the size of the postsynaptic signaling scaffold (PSD) across from the presynaptic terminal. In the final stage of LTP, the changes in synaptic morphology are consolidated by stabilization of actin filaments through actin capping and cross-linking together with the insertion of newly synthesized synaptic proteins (Lynch et al., 2007). Although the different steps of LTP shaping spine morphology and stability are generally understood, the signaling events that coordinate the initial disassembly of the existing synaptic architecture with reassembly of a stronger synaptic connection remain unclear.Neuroligins (NLGs) are a family of four transmembrane postsynaptic adhesion molecules (NLGs 1–4) that form heterotypic adhesions with presynaptic neurexins via an extracellular acetylcholinesterase-like domain (Südhof, 2008). Of the four NLG family members, NLG1 localizes predominantly to excitatory glutamatergic synapses (Song et al., 1999). Both in vitro and in vivo evidence demonstrate that the NLG–neurexin binding interaction is sufficient to promote synapse formation (Südhof, 2008; Chen et al., 2010). However, NLG knockout mice exhibit normal spine density but impaired synaptic transmission, suggesting that NLGs may regulate synaptic function independent of adhesion (Südhof, 2008). In addition to trans-synaptic adhesion mediated by the extracellular domain of NLGs, their short intracellular C-terminal domain (CTD) contains a PDZ binding domain (PBD) that facilitates binding and recruitment of postsynaptic density scaffold proteins, such as PSD95 (Irie et al., 1997; Dresbach et al., 2004). NLG1 is cleaved in an activity-dependent manner, leading to the release of an extracellular fragment that destabilizes synaptic adhesion and of the intracellular CTD (Suzuki et al., 2012).In this issue, Liu et al. focused on how activity-dependent cleavage of NLG1 and the subsequent release of its CTD affect actin organization and spine stability at excitatory synapses. They first observed that NLG1 knockout mouse brains, as well as cultured neurons infected with an shRNA targeting NLG1, exhibit decreased cofilin-S3 phosphorylation when compared with wild-type levels. Cofilin-S3 phosphorylation functions as a marker of mature dendritic spines, as cofilin inactivation results in F-actin assembly and is associated with the later stages of LTP (Calabrese et al., 2014). In addition, the absence of NLG1 prevented dynamic regulation of cofilin phosphorylation in response to KCl-induced neuronal excitation of brain slices, suggesting that cofilin phosphorylation depends on NLG1 both basally and in an activity-dependent manner. Remarkably, incubation with recombinant NLG1-CTD increased spine-associated cofilin phosphorylation in cultured neurons and rescued cofilin phosphorylation in NLG1 knockout mouse brain slices. Using full-length or truncated NLG1 constructs with a wild-type or mutated PDB sequence, Liu et al. (2016) demonstrated that NLG1-induced cofilin phosphorylation depends on both NLG1 cleavage and an intact PBD sequence within the released CTD. As the NLG1-CTD alone induced spine-associated cofilin phosphorylation, the researchers investigated its impact on actin assembly associated with synapse formation and function. In cultured neurons, recombinant NLG1-CTD increased F-actin levels together with spine and synapse formation. Similarly, intravenous injection of NLG1-CTD increased spine density in the CA1 region of the mouse hippocampus. This increased spine and synapse formation resulted in a corresponding increase in the frequency of excitatory postsynaptic currents, which was inhibited by a peptide that blocked cofilin phosphorylation. Together, these results establish that the NLG1-CTD requires cofilin phosphorylation to strengthen synaptic connections, prompting Liu et al. (2016) to investigate the mechanism underlying NLG1-induced cofilin phosphorylation.SPAR is a known regulator of the actin cytoskeleton that is hypothesized to bind to NLG1 (Craig and Kang, 2007). Using brain lysates and HEK293 cells expressing both NLG1 and SPAR, Liu et al. (2016) demonstrated that SPAR interacts with NLG1-CTD via its PBD domain. In brain slices, KCl-mediated excitation, which induces proteolytic cleavage of endogenous NLG1, increased the association of NLG1 and SPAR, suggesting that the interaction occurs in response to activity-dependent release of an intracellular CTD. To test whether this interaction regulates cofilin phosphorylation, Liu et al. (2016) expressed SPAR in HEK293 cells, where it decreased cofilin-S3 phosphorylation. However, incubation with a recombinant NLG1-CTD containing an intact PBD restored cofilin phosphorylation, demonstrating that this interaction alleviates SPAR-mediated repression of cofilin phosphorylation. In neurons, NLG1-CTD reduced the levels of synaptic SPAR, as assessed by both immunofluorescence and Western blotting of purified synaptosomes. SPAR is known to negatively regulate Rap1 signaling, and Rap1 signaling is important for Rac1 activation and spine morphogenesis (Pak et al., 2001; Maillet et al., 2003). In cultured neurons, a Rap1 inhibitor prevented NLG1-CTD–induced cofilin phosphorylation, whereas treatment with recombinant NLG1-CTD without Rap1 inhibition activated Rac1 signaling, leading to phosphorylation of its downstream targets, LIMK1 and cofilin. The results demonstrate that the CTD of NLG1 binds and displaces SPAR from the spine, alleviating its inhibition on Rap1 signaling. In turn, increased Rap1 signaling promotes Rac1 activation, leading to LIMK-1 and cofilin phosphorylation (Fig. 1). Lastly, these NLG-driven changes in actin assembly were found to simultaneously inhibit long-term depression, an activity-dependent reduction in the efficacy of synapses, and facilitate LTP, as determined by whole-cell patch clamping of brain slices incubated with NLG1-CTD.Open in a separate windowFigure 1.NLG’s CTD strengthens the synapse from within through dynamic actin remodeling. Excitatory activation of NMDA receptors (NMDAR) results in sequential cleavage of NLG1 (Suzuki et al., 2012). Liu et al. (2016) describe how the CTD of NLG1 interacts with SPAR, a negative regulator of Rap GTPase activity. This activity-dependent interaction displaces SPAR and alleviates the local inhibition of Rap activity within the dendritic spine. Rap drives a corresponding increase in Rac activation and phosphorylation of its downstream target, the actin regulator cofilin, thereby increasing F-actin filament assembly within spines. These changes in actin organization ultimately result in increased spine density and promote LTP.This work provides important insights into the mechanism by which NLG1 impacts synapse development and function by highlighting a critical role for SPAR in the regulation of actin assembly mediating synaptic strengthening. Interestingly, the temporal delay between the release of the NLG1-CTD and the subsequent sequestration of SPAR from the PSD could serve to distinguish an early disassembly phase following excitatory stimulation from later LTP consolidation, which is known to rely on both Rac1 activation (Rex et al., 2009) and cofilin phosphorylation (Bosch et al., 2014). Furthermore, it will be of interest to determine whether NLG1’s CTD affects the localization of other proteins known to bind its PBD, such as PSD95 (Irie et al., 1997), and whether these dynamic rearrangements at the postsynaptic scaffold also serve to simultaneously promote actin assembly while alleviating SPAR-mediated negative regulation of actin remodeling. For example, NLG1 has been shown to interact with Kalirin-7 (Owczarek et al., 2015), an activator of Rac1 that binds to PSD95 at the synapse; however, binding to PSD95 reduces Kalirin-7–mediated activation of Rac1 (Penzes et al., 2001). It is therefore attractive to speculate that the activity-dependent release of protein fragments, such as the CTD of NLG1, might alter postsynaptic density interactions that further promote localized Rac1-driven F-actin assembly. Consistent with this hypothesis, adhesion disassembly triggered by the extracellular domain of NLG1’s binding partner (β-neurexin) increases Rac1 activation (Owczarek et al., 2015). Ultimately, more work is necessary to determine how the strengthening effects of the intracellular CTD compete with the destabilizing effects of the extracellular domain (Suzuki et al., 2012). Recent research demonstrates that CAMKII phosphorylates and increases NLG1 surface expression in response to NMDA receptor activation (Bemben et al., 2014). If this phosphorylation event protects NLG1 from cleavage, it could serve to stabilize an adhesive pool of NLG1 while allowing for the release of the CTD from an unprotected population. Alternatively, this phosphorylation event could serve to recruit new NLG1 proteins to the synapse later in the LTP process when adhesions are reestablished. Further research is needed to understand how the adhesive and intracellular signaling capabilities of NLG1 are balanced at discrete stages of synaptic plasticity, and in particular how phosphorylation of NLG1 regulates both its surface expression as well as its cleavage.Consistent with the multiple roles of NLGs in modulating synaptic architecture, it is not surprising that NLG mutations have been implicated in diverse cognitive and neurodevelopmental disorders, such as Alzheimer’s disease and autism (Südhof, 2008; Tristán-Clavijo et al., 2015). In light of this study, it will be interesting to determine how disease-associated NLG mutations contribute to both synaptic adhesion as well as stabilization of the actin cytoskeleton that supports synaptic strengthening. This is particularly important because both Alzheimer’s disease and autism-associated NLG mutant proteins exhibit decreased surface expression (Chubykin et al., 2005; Tristán-Clavijo et al., 2015), although the autism-associated mutant NLG proteins present at the cell surface still promote synapse formation (Chubykin et al., 2005). However, the decreased postsynaptic NLG pool could impair subsequent activity-dependent synaptic strengthening. Likewise, understanding whether binding of the postsynaptic scaffolding protein Shank3 to the CTD of NLG1 (Arons et al., 2012) affects NLG1 cleavage could provide insights into the mechanism by which Shank3 affects activity-dependent synaptic remodeling in autism pathogenesis. The work by Liu et al. (2016), demonstrating that adhesion disassembly coordinates subsequent actin assembly underlying synaptic strengthening, takes an important step toward shedding light on the altered synaptic plasticity underlying both complex neurodevelopmental and neurodegenerative pathologies.     

A segmental labeling strategy for unambiguous determination of domain–domain interactions of large multi-domain proteins

NMR structural determination of large multi-domain proteins is a challenging task due to significant spectral overlap with a particular difficulty in unambiguous identification of domain–domain interactions. Segmental labeling is a NMR strategy that allows for isotopically labeling one domain and leaves the other domain unlabeled. This significantly simplifies spectral overlaps and allows for quick identification of domain–domain interaction. Here, a novel segmental labeling strategy is presented for detection of inter-domain NOEs. To identify domain–domain interactions in human apolipoprotein E (apoE), a multi-domain, 299-residues α-helical protein, on-column expressed protein ligation was utilized to generate a segmental-labeled apoE samples in which the N-terminal (NT-) domain was ²H(99%)/¹⁵N-labeled whereas the C-terminal (CT-) domain was either ¹⁵N- or ¹⁵N/¹³C-labeled. 3-D ¹⁵N-edited NOESY spectra of these segmental-labeled apoE samples allow for direct observation of the inter-domain NOEs between the backbone amide protons of the NT-domain and the aliphatic protons of the CT-domain. This straightforward approach permits unambiguous identification of 78 inter-domain NOEs, enabling accurate definition of the relative positions of both the NT- and the CT-domains and determination of the NMR structure of apoE.     

A life cycle method for assessment of a colliery’s eco-indicator

Global Scope and Background  The study was aimed at presenting the methodology of the process eco-indicator, in relation to hard coal mines, and thereby making evaluation of the impact of the mine’s coal extraction process on the environment. The life cycle of a mine is made up of three phases: opening and developing the mine’s deposit, extraction of the mine’s deposit, closing the mine. Methods  The assessment of environmental influence of mining operation of a colliery was executed on a basis of the life cycle analysis, in accordance with the standard series PN-EN 14040. The environmental loads caused by individual unit processes were calculated by means of the aforementioned methodology with division into the basic influence categories: human health, ecosystem quality and natural resources. The obtained values of eco-indicators for the individual unit processes made it possible to compare the unit-process-caused environmental loads. Mean values of the eco-indicators of the individual unit processes were calculated by means of the inventory analysis covering 38 collieries. Next, these indicators were used to compare environmental load values by each similar process in a colliery. A total eco-indicator was calculated for colliery by summing up the eco-indicators of the individual unit processes. The eco-indicators, structured as above, were calculated for the phase of opening out a deposit and for the phase of extraction. Results and Discussion  The model mine in the phase of extraction of a deposit causes a total environmental load which expressed in points of the eco-indicator 99 amounts to 23.9 [MEw]. In the ‘human health’ category losses amount to 8.4 per cent, in the ‘quality of ecosystem’ 0.6 per cent and in the ‘resourses’ category 91 per cent. The greatest losses in all categories are caused by the process of getting body of coal and the next greatest ones are:

A novel fractionation method of the rough ER integral membrane proteins; Resident proteins versus exported proteins?

We treated the high salt‐washed canine pancreatic rough ER (KRM) with 0.18% Triton X‐100, separated the extract from the residual membrane (0.18%Tx KRM), and processed the extract with SM‐2 beads to recover membrane proteins in proteoliposomes. To focus on integral membrane proteins, KRM, 0.18%Tx KRM and proteoliposomes were subjected to sodium carbonate treatment, and analyzed by 2‐D gel electrophoresis. Consequently we found that a distinct group of integral membrane protein of KRM preferentially extracted from the membrane and recovered in proteoliposomes did exist, while majority of KRM integral membrane proteins were fractionated in 0.18%Tx KRM, which retained the basic structure and functions of KRM. Protein identification showed that the former group was enriched with proteins exported from the ER and the latter group comprised mostly of ER resident proteins. This result will potentially affect the prevailing view of the ER membrane structure as well as protein sorting from the ER.