Competition-based model of pheromone component ratio detection in the moth

For some moth species, especially those closely interrelated and sympatric, recognizing a specific pheromone component concentration ratio is essential for males to successfully locate conspecific females. We propose and determine the properties of a minimalist competition-based feed-forward neuronal model capable of detecting a certain ratio of pheromone components independently of overall concentration. This model represents an elementary recognition unit for the ratio of binary mixtures which we propose is entirely contained in the macroglomerular complex (MGC) of the male moth. A set of such units, along with projection neurons (PNs), can provide the input to higher brain centres. We found that (1) accuracy is mainly achieved by maintaining a certain ratio of connection strengths between olfactory receptor neurons (ORN) and local neurons (LN), much less by properties of the interconnections between the competing LNs proper. An exception to this rule is that it is beneficial if connections between generalist LNs (i.e. excited by either pheromone component) and specialist LNs (i.e. excited by one component only) have the same strength as the reciprocal specialist to generalist connections. (2) successful ratio recognition is achieved using latency-to-first-spike in the LN populations which, in contrast to expectations with a population rate code, leads to a broadening of responses for higher overall concentrations consistent with experimental observations. (3) when longer durations of the competition between LNs were observed it did not lead to higher recognition accuracy

Internal Cholinergic Regulation of Learning and Recall in a Model of Olfactory Processing

In the olfactory system, cholinergic modulation has been associated with contrast modulation and changes in receptive fields in the olfactory bulb, as well the learning of odor associations in olfactory cortex. Computational modeling and behavioral studies suggest that cholinergic modulation could improve sensory processing and learning while preventing pro-active interference when task demands are high. However, how sensory inputs and/or learning regulate incoming modulation has not yet been elucidated. We here use a computational model of the olfactory bulb, piriform cortex (PC) and horizontal limb of the diagonal band of Broca (HDB) to explore how olfactory learning could regulate cholinergic inputs to the system in a closed feedback loop. In our model, the novelty of an odor is reflected in firing rates and sparseness of cortical neurons in response to that odor and these firing rates can directly regulate learning in the system by modifying cholinergic inputs to the system. In the model, cholinergic neurons reduce their firing in response to familiar odors—reducing plasticity in the PC, but increase their firing in response to novel odor—increasing PC plasticity. Recordings from HDB neurons in awake behaving rats reflect predictions from the model by showing that a subset of neurons decrease their firing as an odor becomes familiar

Zoonotic and pandemic influenza A viruses: lessons from H5N1 and H2N2

Influenza A viruses can be directly transmitted from animals to humans (zoonotic viruses), cause worldwide outbreaks (pandemic viruses) or infect people annually (seasonal viruses). Influenza A viruses that are transmitted efficiently from one person to another have in common that they can spread via the air. We have studied zoonotic H5N1 and pandemic H2N2 influenza viruses with respect to their evolution over time, their potential to transmit via the air, and the virus properties that are required to be efficiently transmitted via the air. From 1997 onwards, H5N1 influenza viruses have occasionally infected humans resulting in severe illness and several deaths. To investigate if this new zoonotic virus had the capacity to spread via the air, we adapted this virus to ferrets, an animal model often used to study airborne transmission of influenza A viruses. We have shown that as little as five mutations in the genetic material of the virus, changing three virus properties, are sufficient for the virus to transmit via the air. Since influenza A viruses evolve constantly, our immune system cannot protect us from infections with new influenza viruses that might emerge in the future. H2N2 influenza virus has caused a pandemic in 1957 and caused seasonal outbreaks in humans until 1968. We have shown that the pandemic potential of H2H2 influenza viruses circulating in birds is low. Furthermore, we have investigated the genetic diversity of H2N2 influenza viruses over time and have determined the mutations that had an effect on recognition by the immune system

Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics.

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives

Neurogenesis Drives Stimulus Decorrelation in a Model of the Olfactory Bulb

The reshaping and decorrelation of similar activity patterns by neuronal networks can enhance their discriminability, storage, and retrieval. How can such networks learn to decorrelate new complex patterns, as they arise in the olfactory system? Using a computational network model for the dominant neural populations of the olfactory bulb we show that fundamental aspects of the adult neurogenesis observed in the olfactory bulb -- the persistent addition of new inhibitory granule cells to the network, their activity-dependent survival, and the reciprocal character of their synapses with the principal mitral cells -- are sufficient to restructure the network and to alter its encoding of odor stimuli adaptively so as to reduce the correlations between the bulbar representations of similar stimuli. The decorrelation is quite robust with respect to various types of perturbations of the reciprocity. The model parsimoniously captures the experimentally observed role of neurogenesis in perceptual learning and the enhanced response of young granule cells to novel stimuli. Moreover, it makes specific predictions for the type of odor enrichment that should be effective in enhancing the ability of animals to discriminate similar odor mixtures

Relative Protein Lifetime Measurement in Plants Using Tandem Fluorescent Protein Timers

Targeted protein degradation plays a wide range of important roles in plant growth and development, but analyzing protein turnover in vivo is technically challenging. Until recently, there has been no straightforward methodology for quantifying protein dynamics at subcellular resolution during cellular transitions in plants. A tandem fluorescent protein timer (tFT) is a fusion of two different fluorescent proteins with distinct fluorophore maturation kinetics, which allows estimation of relative protein age from the ratio of fluorescence intensities of the two fluorescent proteins. Here, we describe approaches to use this technology to report relative protein lifetime in both transient and stable plant transformation systems. tFTs enable in vivo, real-time protein lifetime assessment within subcellular compartments and across tissues, permitting the analysis of protein degradation dynamics in response to stresses or developmental cues and in different genetic backgrounds

Emergence of Connectivity Motifs in Networks of Model Neurons with Short- and Long-term Plastic Synapses

Recent evidence in rodent cerebral cortex and olfactory bulb suggests that short-term dynamics of excitatory synaptic transmission is correlated to stereotypical connectivity motifs. It was observed that neurons with short-term facilitating synapses form predominantly reciprocal pairwise connections, while neurons with short-term depressing synapses form unidirectional pairwise connections. The cause of these structural differences in synaptic microcircuits is unknown. We propose that these connectivity motifs emerge from the interactions between short-term synaptic dynamics (SD) and long-term spike-timing dependent plasticity (STDP). While the impact of STDP on SD was shown in vitro, the mutual interactions between STDP and SD in large networks are still the subject of intense research. We formulate a computational model by combining SD and STDP, which captures faithfully short- and long-term dependence on both spike times and frequency. As a proof of concept, we simulate recurrent networks of spiking neurons with random initial connection efficacies and where synapses are either all short-term facilitating or all depressing. For identical background inputs, and as a direct consequence of internally generated activity, we find that networks with depressing synapses evolve unidirectional connectivity motifs, while networks with facilitating synapses evolve reciprocal connectivity motifs. This holds for heterogeneous networks including both facilitating and depressing synapses. Our study highlights the conditions under which SD-STDP might the correlation between facilitation and reciprocal connectivity motifs, as well as between depression and unidirectional motifs. We further suggest experiments for the validation of the proposed mechanism

Determination of nutrient salts by automatic methods both in seawater and brackish water: the phosphate blank

9 páginas, 2 tablas, 2 figurasThe main inconvenience in determining nutrients in seawater by automatic methods is simply solved: the preparation of a suitable blank which corrects the effect of the refractive index change on the recorded signal. Two procedures are proposed, one physical (a simple equation to estimate the effect) and the other chemical (removal of the dissolved phosphorus with ferric hydroxide).Support for this work came from CICYT (MAR88-0245 project) and Conselleria de Pesca de la Xunta de GaliciaPeer reviewe

Elucidating variations in the nucleotide sequence of Ebola virus associated with increasing pathogenicity

Background Ebolaviruses cause a severe and often fatal haemorrhagic fever in humans, with some species such as Ebola virus having case fatality rates approaching 90%. Currently, the worst Ebola virus outbreak since the disease was discovered is occurring in West Africa. Although thought to be a zoonotic infection, a concern is that with increasing numbers of humans being infected, Ebola virus variants could be selected which are better adapted for human-to-human transmission. Results To investigate whether genetic changes in Ebola virus become established in response to adaptation in a different host, a guinea pig model of infection was used. In this experimental system, guinea pigs were infected with Ebola virus (EBOV), which initially did not cause disease. To simulate transmission to uninfected individuals, the virus was serially passaged five times in naïve animals. As the virus was passaged, virulence increased and clinical effects were observed in the guinea pig. An RNAseq and consensus mapping approach was then used to evaluate potential nucleotide changes in the Ebola virus genome at each passage. Conclusions Upon passage in the guinea pig model, EBOV become more virulent, RNA editing and also coding changes in key proteins become established. The data suggest that the initial evolutionary trajectory of EBOV in a new host can lead to a gain in virulence. Given the circumstances of the sustained transmission of EBOV in the current outbreak in West Africa, increases in virulence may be associated with prolonged and uncontrolled epidemics of EBOV

Queen mandibular pheromone: questions that remain to be resolved

The discovery of ‘queen substance’, and the subsequent identification and synthesis of keycomponents of queen mandibular pheromone, has been of significant importance to beekeepers and to thebeekeeping industry. Fifty years on, there is greater appreciation of the importance and complexity of queenpheromones, but many mysteries remain about the mechanisms through which pheromones operate. Thediscovery of sex pheromone communication in moths occurred within the same time period, but in this case,intense pressure to find better means of pest management resulted in a remarkable focusing of research activityon understanding pheromone detection mechanisms and the central processing of pheromone signals in themoth. We can benefit from this work and here, studies on moths are used to highlight some of the gaps in ourknowledge of pheromone communication in bees. A better understanding of pheromone communication inhoney bees promises improved strategies for the successful management of these extraordinary animals