Insecticide resistance in Bemisia tabaci from Cyprus

Abstract A comprehensive study on the Bemisia tabaci (biotype B) resistance to neonicotinoid insecticides imidacloprid, acetamiprid and thiamethoxam, and pyrethroid bifenthrin was conducted in Cyprus. The resistance level to eight field‐collected B. tabaci populations was investigated. The activities of enzymes involved in metabolic detoxification and the frequencies of pyrethroid and organophosphates target site resistance mutations were determined. Moderate to high levels of resistance were detected for imidacloprid (resistance factor [RF] 77–392) and thiamethoxam (RF 50–164) while low resistance levels were observed for acetamiprid (RF 7–12). Uniform responses by the Cypriot whiteflies could be observed against all neonicotinoid insecticides. No cross‐resistance between the neonicotinoids was detected as well as no association with the activity of the P450 microsomal oxidases. Only imidacloprid resistance correlated with carboxylesterase activity. Low to extremely high resistance was observed for insecticide bifenthrin (RF 49–1 243) which was associated with the frequency of the resistant allele in the sodium channel gene but not with the activity of the detoxification enzymes. Finally, the F331W mutation in the acetylcholinesterase enzyme ace1 gene was fixed in all B. tabaci populations from Cyprus.     

Ion beam radiobiology and cancer: Time to update ourselves

High-energy protons and carbon ions exhibit an inverse dose profile allowing for increased energy deposition with penetration depth. Additionally, heavier ions like carbon beams have the advantage of a markedly increased biological effectiveness characterized by enhanced ionization density in the individual tracks of the heavy particles, where DNA damage becomes clustered and therefore more difficult to repair, but is restricted to the end of their range. These superior biophysical and biological profiles of particle beams over conventional radiotherapy permit more precise dose localization and make them highly attractive for treating anatomically complex and radioresistant malignant tumors but without increasing the severe side effects in the normal tissue. More than half a century since Wilson proposed their use in cancer therapy, the effects of particle beams have been extensively investigated and the biological complexity of particle beam irradiation begins to unfold itself. The goal of this review is to provide an as comprehensive and up-to-date summary as possible of the different radiobiological aspects of particle beams for effective application in cancer treatment.     

Specificity profile of NAT/NCS2 purine transporters in Sinorhizobium (Ensifer) meliloti

Sinorhizobium (Ensifer) meliloti is a model example of a soil alpha-proteobacterium which induces the formation of nitrogen-fixing symbiotic nodules on the legume roots. In contrast to all other rhizobacterial species, S. meliloti contains multiple homologs of nucleobase transporter genes that belong to NAT/NCS2 family (Nucleobase-Ascorbate Transporter/Nucleobase-Cation Symporter-2). We analyzed functionally all (six) relevant homologs of S. meliloti 1,021 using Escherichia coli K-12 as a host and found that five of them are high-affinity transporters for xanthine (SmLL9), uric acid (SmLL8, SmLL9, SmX28), adenine (SmVC3, SmYE1), guanine (SmVC3), or hypoxanthine (SmVC3). Detailed analysis of substrate profiles showed that two of these transporters display enlarged specificity (SmLL9, SmVC3). SmLL9 is closely related in sequence with the xanthine-specific XanQ of E. coli. We subjected SmLL9 to rationally designed site-directed mutagenesis and found that the role of key binding-site residues of XanQ is conserved in SmLL9, whereas a single amino-acid change (S93N) converts the xanthine/uric-acid transporter SmLL9 to a xanthine-preferring variant, due to disruption of an essential hydrogen bond with the C8 oxygen of uric acid. The results highlight the presence of several different purine nucleobase transporters in S. meliloti and imply that the purine transport might be important in the nodule symbiosis involving S. meliloti.     

Fast-evolving noncoding sequences in the human genome

Background

Gene regulation is considered one of the driving forces of evolution. Although protein-coding DNA sequences and RNA genes have been subject to recent evolutionary events in the human lineage, it has been hypothesized that the large phenotypic divergence between humans and chimpanzees has been driven mainly by changes in gene regulation rather than altered protein-coding gene sequences. Comparative analysis of vertebrate genomes has revealed an abundance of evolutionarily conserved but noncoding sequences. These conserved noncoding (CNC) sequences may well harbor critical regulatory variants that have driven recent human evolution.

Results

Here we identify 1,356 CNC sequences that appear to have undergone dramatic human-specific changes in selective pressures, at least 15% of which have substitution rates significantly above that expected under neutrality. The 1,356 'accelerated CNC' (ANC) sequences are enriched in recent segmental duplications, suggesting a recent change in selective constraint following duplication. In addition, single nucleotide polymorphisms within ANC sequences have a significant excess of high frequency derived alleles and high F _ST values relative to controls, indicating that acceleration and positive selection are recent in human populations. Finally, a significant number of single nucleotide polymorphisms within ANC sequences are associated with changes in gene expression. The probability of variation in an ANC sequence being associated with a gene expression phenotype is fivefold higher than variation in a control CNC sequence.

Conclusion

Our analysis suggests that ANC sequences have until very recently played a role in human evolution, potentially through lineage-specific changes in gene regulation.     

Improved Estimation and Interpretation of Correlations in Neural Circuits

Ambitious projects aim to record the activity of ever larger and denser neuronal populations in vivo. Correlations in neural activity measured in such recordings can reveal important aspects of neural circuit organization. However, estimating and interpreting large correlation matrices is statistically challenging. Estimation can be improved by regularization, i.e. by imposing a structure on the estimate. The amount of improvement depends on how closely the assumed structure represents dependencies in the data. Therefore, the selection of the most efficient correlation matrix estimator for a given neural circuit must be determined empirically. Importantly, the identity and structure of the most efficient estimator informs about the types of dominant dependencies governing the system. We sought statistically efficient estimators of neural correlation matrices in recordings from large, dense groups of cortical neurons. Using fast 3D random-access laser scanning microscopy of calcium signals, we recorded the activity of nearly every neuron in volumes 200 μm wide and 100 μm deep (150–350 cells) in mouse visual cortex. We hypothesized that in these densely sampled recordings, the correlation matrix should be best modeled as the combination of a sparse graph of pairwise partial correlations representing local interactions and a low-rank component representing common fluctuations and external inputs. Indeed, in cross-validation tests, the covariance matrix estimator with this structure consistently outperformed other regularized estimators. The sparse component of the estimate defined a graph of interactions. These interactions reflected the physical distances and orientation tuning properties of cells: The density of positive ‘excitatory’ interactions decreased rapidly with geometric distances and with differences in orientation preference whereas negative ‘inhibitory’ interactions were less selective. Because of its superior performance, this ‘sparse+latent’ estimator likely provides a more physiologically relevant representation of the functional connectivity in densely sampled recordings than the sample correlation matrix.