Trait differences among discrete morphs of a color polymorphic lizard, Podarcis erhardii
Color polymorphism defies evolutionary expectations as striking phenotypic variation is maintained within a single species. Color and other traits mediate social interactions, and stable polymorphism within a population is hypothesized to be related to correlational selection of other phenotypic traits among color morphs. Here, we report on a previously unknown throat color polymorphism in the Aegean Wall Lizard (Podarcis erhardii) and examine morph-correlated differences in traits important to social behavior and communication: maximum bite force capacity and chemical signal profile. We find that both sexes of P. erhardii have three color morphs: orange, yellow, and white. Moreover, orange males are significantly larger and tend to bite harder than yellow and white males. Although the established color polymorphism only partially matches the observed intraspecific variation in chemical signal signatures, the chemical profile of the secretions of orange males is significantly divergent from that of white males. Our findings suggest that morph colors are related to differences in traits that are crucial for social interactions and competitive ability, illustrating the need to look beyond color when studying polymorphism evolution.
Brock et al. (2020) Trait differences among discrete morphs of a color polymorphic lizard, Podarcis erhardii. PeerJ 8:e10284 https://doi.org/10.7717/peerj.10284
Robustness analysis in an inter-cities mobility network: modeling municipal, state and federal initiatives as failures and attacks toward SARS-CoV-2 containment
We present a robustness analysis of an inter-cities mobility complex network, motivated by the challenge of the COVID-19 pandemic and the seek for proper containment strategies. Brazilian data from 2016 are used to build a network with more than five thousand cities (nodes) and twenty-seven states with the edges representing the weekly flow of people between cities via terrestrial transports. Nodes are systematically isolated (removed from the network) either at random (failures) or guided by specific strategies (targeted attacks), and the impacts are assessed with three metrics: the number of components, the size of the giant component, and the total remaining flow of people. We propose strategies to identify which regions should be isolated first and their impact on people mobility. The results are compared with the so-called reactive strategy, which consists of isolating regions ordered by the date the first case of COVID-19 appeared. We assume that the nodes’ failures abstract individual municipal and state initiatives that are independent and possess a certain level of unpredictability. Differently, the targeted attacks are related to centralized strategies led by the federal government in agreement with municipalities and states. Removing a node means completely restricting the mobility of people between the referred city/state and the rest of the network. Results reveal that random failures do not cause a high impact on mobility restraint, but the coordinated isolation of specific cities with targeted attacks is crucial to detach entire network areas and thus prevent spreading. Moreover, the targeted attacks perform better than the reactive strategy for the three analyzed robustness metrics.
Spatial and Geographic Information Science
Freitas et al. (2020) Robustness analysis in an inter-cities mobility network: modeling municipal, state and federal initiatives as failures and attacks toward SARS-CoV-2 containment. PeerJ 8:e10287 https://doi.org/10.7717/peerj.10287
Deep-learning convolutional neural networks with transfer learning accurately classify COVID-19 lung infection on portable chest radiographs
Portable chest X-ray (pCXR) has become an indispensable tool in the management of Coronavirus Disease 2019 (COVID-19) lung infection. This study employed deep-learning convolutional neural networks to classify COVID-19 lung infections on pCXR from normal and related lung infections to potentially enable more timely and accurate diagnosis. This retrospect study employed deep-learning convolutional neural network (CNN) with transfer learning to classify based on pCXRs COVID-19 pneumonia (N = 455) on pCXR from normal (N = 532), bacterial pneumonia (N = 492), and non-COVID viral pneumonia (N = 552). The data was randomly split into 75% training and 25% testing, randomly. A five-fold cross-validation was used for the testing set separately. Performance was evaluated using receiver-operating curve analysis. Comparison was made with CNN operated on the whole pCXR and segmented lungs. CNN accurately classified COVID-19 pCXR from those of normal, bacterial pneumonia, and non-COVID-19 viral pneumonia patients in a multiclass model. The overall sensitivity, specificity, accuracy, and AUC were 0.79, 0.93, and 0.79, 0.85 respectively (whole pCXR), and were 0.91, 0.93, 0.88, and 0.89 (CXR of segmented lung). The performance was generally better using segmented lungs. Heatmaps showed that CNN accurately localized areas of hazy appearance, ground glass opacity and/or consolidation on the pCXR. Deep-learning convolutional neural network with transfer learning accurately classifies COVID-19 on portable chest X-ray against normal, bacterial pneumonia or non-COVID viral pneumonia. This approach has the potential to help radiologists and frontline physicians by providing more timely and accurate diagnosis.
Kikkisetti et al. (2020) Deep-learning convolutional neural networks with transfer learning accurately classify COVID-19 lung infection on portable chest radiographs. PeerJ 8:e10309 https://doi.org/10.7717/peerj.10309
An updated evolutionary study of the Notch family reveals a new ancient origin and novel invariable motifs as potential pharmacological targets
Notch family proteins play a key role in a variety of developmental processes by controlling cell fate decisions and operating in a great number of biological processes in several organ systems, such as hematopoiesis, somatogenesis, vasculogenesis, neurogenesis and homeostasis. The Notch signaling pathway is crucial for the majority of developmental programs and regulates multiple pathogenic processes. Notch family receptors’ activation has been largely related to its multiple effects in sustaining oncogenesis. The Notch signaling pathway constitutes an ancient and conserved mechanism for cell to cell communication. Much of what is known about Notch family proteins function comes from studies done in Caenorhabditis Elegans and Drosophila Melanogaster. Although, human Notch homologs had also been identified, the molecular mechanisms which modulate the Notch signaling pathway remained substantially unknown. In this study, an updated evolutionary analysis of the Notch family members among 603 different organisms of all kingdoms, from bacteria to humans, was performed in order to discover key regions that have been conserved throughout evolution and play a major role in the Notch signaling pathway. The major goal of this study is the presentation of a novel updated phylogenetic tree for the Notch family as a reliable phylogeny “map”, in order to correlate information of the closely related members and identify new possible pharmacological targets that can be used in pathogenic cases, including cancer.
Vlachakis et al. (2020) An updated evolutionary study of the Notch family reveals a new ancient origin and novel invariable motifs as potential pharmacological targets. PeerJ 8:e10334 https://doi.org/10.7717/peerj.10334
Geographic variation in the skull morphology of the lesser grison (Galictis cuja: Carnivora, Mustelidae) from two Brazilian ecoregions
Background The lesser grison (Galictis cuja) is one of the least known carnivores in the Neotropical region. Its wide geographical occurrence and range of habitats could lead to morphological variations along its distribution. So, this study aimed to investigate the variation in skull shape and size of this species, by testing the existence of ecotypes adapted to their respective environments (Uruguayan savanna and Atlantic Forest), as well as its relationship with selected abiotic variables. Methods The skulls of 52 museum specimens were photographed in the ventral, dorsal, and lateral views, and were analyzed using geometric morphometric techniques. Results We found sexual size dimorphism, with males being larger than females. The shape variation between sexes, as well as between ecoregions, is mostly explained by the effect of allometry. The specimens from Uruguayan savanna are larger than the ones from the Atlantic Forest. Size variation was also significantly correlated to latitude, temperature and precipitation patterns. No correlation between skull shape with geographical distance was detected. Discussion Morphometric measurements and diet data of lesser grison in regions from higher latitudes than our sampling show a tendency to heavier individuals, and the consumption of bigger prey compared to Uruguayan savanna. The results indicated the smaller specimens associated to low variability in annual temperature, congruent to Atlantic Forest region. An explanation for observed variation may be related to the “resource rule” but, due the minimal natural history information regards this species, we can just speculate about this.
Migliorini et al. (2020) Geographic variation in the skull morphology of the lesser grison (Galictis cuja: Carnivora, Mustelidae) from two Brazilian ecoregions. PeerJ 8:e9388 https://doi.org/10.7717/peerj.9388
A new nurse frog (Anura: Allobates) from Brazilian Amazonia with a remarkably fast multi-noted advertisement call
Nurse frogs (Aromobatidae: Allobates) are probably the most extensively studied genus by taxonomists in Brazilian Amazonia. The southwestern portion of Amazonia is the most species-rich: as many as seven species may occur in sympatry at a single locality. In this study, we describe a new species of nurse frog from this region. The description integrates data from larval and adult morphology, advertisement calls and DNA sequences. Allobates velocicantus sp. nov. is distinguished from other Allobates mainly by the absence of hourglass-shaped dark marks on the dorsum and dark transverse bars on the thigh; a throat that is white centrally and yellow marginally; basal webbing on toes II and III; finger I longer than finger II; and an advertisement call composed of 66–138 pulsed notes with a note duration of 5–13 ms, inter-note intervals of 10–18 ms and a dominant frequency of 5,512–6,158 Hz. Tadpoles of the new species have 3–4 short, rounded papillae on the anterior labium, 16–23 papillae on the posterior labium, and a labial keratodont row formula 2(2)/3(1). This is the fifth species of Allobates described from the state of Acre, southwestern Brazilian Amazonia.
Souza et al. (2020) A new nurse frog (Anura: Allobates) from Brazilian Amazonia with a remarkably fast multi-noted advertisement call. PeerJ 8:e9979 https://doi.org/10.7717/peerj.9979
Silicon flow from root to shoot in pepper: a comprehensive in silico analysis reveals a potential linkage between gene expression and hormone signaling that stimulates plant growth and metabolism
Background Silicon (Si) is categorized as a quasi-essential element for plants thanks to the benefits on growth, development and metabolism in a hormetic manner. Si uptake is cooperatively mediated by Lsi1 and Lsi2. Nevertheless, Lsi channels have not yet been identified and characterized in pepper (Capsicum annuum), while genes involved in major physiological processes in pepper are Si-regulated. Furthermore, Si and phytohormones may act together in regulating plant growth, metabolism and tolerance against stress. Our aim was to identify potential synergies between Si and phytohormones stimulating growth and metabolism in pepper, based on in silico data. Methods We established a hydroponic system to test the effect of Si (0, 60, 125 and 250 mg L−1 Si) on the concentrations of this element in different pepper plant tissues. We also performed an in silico analysis of putative Lsi genes from pepper and other species, including tomato (Solanum lycopersicum), potato (Solanum tuberosum) and Arabidopsis thaliana, to look for cis-acting elements responsive to phytohormones in their promoter regions. With the Lsi1 and Lsi2 protein sequences from various plant species, we performed a phylogenetic analysis. Taking into consideration the Lsi genes retrieved from tomato, potato and Arabidopsis, an expression profiling analysis in different plant tissues was carried out. Expression of Si-regulated genes was also analyzed in response to phytohormones and different plant tissues and developmental stages in Arabidopsis. Results Si concentrations in plant tissues exhibited the following gradient: roots > stems > leaves. We were able to identify 16 Lsi1 and three Lsi2 genes in silico in the pepper genome, while putative Lsi homologs were also found in other plant species. They were mainly expressed in root tissues in the genomes analyzed. Both Lsi and Si-regulated genes displayed cis-acting elements responsive to diverse phytohormones. In Arabidopsis, Si-regulated genes were transcriptionally active in most tissues analyzed, though at different expressed levels. From the set of Si-responsive genes, the NOCS2 gene was highly expressed in germinated seeds, whereas RABH1B, and RBCS-1A, were moderately expressed in developed flowers. All genes analyzed showed responsiveness to phytohormones and phytohormone precursors. Conclusion Pepper root cells are capable of absorbing Si, but small amounts of this element are transported to the upper parts of the plant. We could identify putative Si influx (Lsi1) and efflux (Lsi2) channels that potentially participate in the absorption and transport of Si, since they are mainly expressed in roots. Both Lsi and Si-regulated genes exhibit cis-regulatory elements in their promoter regions, which are involved in phytohormone responses, pointing to a potential connection among Si, phytohormones, plant growth, and other vital physiological processes triggered by Si in pepper.
Gómez-Merino et al. (2020) Silicon flow from root to shoot in pepper: a comprehensive in silico analysis reveals a potential linkage between gene expression and hormone signaling that stimulates plant growth and metabolism. PeerJ 8:e10053 https://doi.org/10.7717/peerj.10053
A model of k-mer surprisal to quantify local sequence information content surrounding splice regions
Molecular sequences carry information. Analysis of sequence conservation between homologous loci is a proven approach with which to explore the information content of molecular sequences. This is often done using multiple sequence alignments to support comparisons between homologous loci. These methods therefore rely on sufficient underlying sequence similarity with which to construct a representative alignment. Here we describe a method using a formal metric of information, surprisal, to analyse biological sub-sequences without alignment constraints. We applied our model to the genomes of five different species to reveal similar patterns across a panel of eukaryotes. As the surprisal of a sub-sequence is inversely proportional to its occurrence within the genome, the optimal size of the sub-sequences was selected for each species under consideration. With the model optimized, we found a strong correlation between surprisal and CG dinucleotide usage. The utility of our model was tested by examining the sequences of genes known to undergo splicing. We demonstrate that our model can identify biological features of interest such as known donor and acceptor sites. Analysis across all annotated coding exon junctions in Homo sapiens reveals the information content of coding exons to be greater than the surrounding intron regions, a consequence of increased suppression of the CG dinucleotide in intronic space. Sequences within coding regions proximal to exon junctions exhibited novel patterns within DNA and coding mRNA that are not a function of the encoded amino acid sequence. Our findings are consistent with the presence of secondary information encoding features such as DNA and RNA binding sites, multiplexed through the coding sequence and independent of the information required to define the corresponding amino-acid sequence. We conclude that surprisal provides a complementary methodology with which to locate regions of interest in the genome, particularly in situations that lack an appropriate multiple sequence alignment.
Humphrey et al. (2020) A model of k-mer surprisal to quantify local sequence information content surrounding splice regions. PeerJ 8:e10063 https://doi.org/10.7717/peerj.10063
Mortality of native and invasive ladybirds co-infected by ectoparasitic and entomopathogenic fungi
Harmonia axyridis is an invasive alien ladybird in North America and Europe. Studies show that multiple natural enemies are using Ha. axyridis as a new host. However, thus far, no research has been undertaken to study the effects of simultaneous infection by multiple natural enemies on Ha. axyridis. We hypothesized that high thallus densities of the ectoparasitic fungus Hesperomyces virescens on a ladybird weaken the host’s defenses, thereby making it more susceptible to infection by other natural enemies. We examined mortality of the North American-native Olla v-nigrum and Ha. axyridis co-infected with He. virescens and an entomopathogenic fungus—either Beauveria bassiana or Metarhizium brunneum. Laboratory assays revealed that He. virescens-infected O. v-nigrum individuals are more susceptible to entomopathogenic fungi, but Ha. axyridis does not suffer the same effects. This is in line with the enemy release hypothesis, which predicts that invasive alien species in new geographic areas experience reduced regulatory effects from natural enemies compared to native species. Considering our results, we can ask how He. virescens affects survival when confronted by other pathogens that previously had little impact on Ha. axyridis.
Haelewaters et al. (2020) Mortality of native and invasive ladybirds co-infected by ectoparasitic and entomopathogenic fungi. PeerJ 8:e10110 https://doi.org/10.7717/peerj.10110
Effects of food hydrocolloids on quality attributes of extruded red Jasmine rice noodle
The aim of this study was to examine the quality characteristics of extruded red Jasmine rice flour (RJF) noodle that had been prepared with hydrocolloids, namely guar gum (GG), carboxymethyl cellulose (CMC), and xanthan gum (XG) at the concentrations of 0.0 (control sample), 0.2, and 0.4% (w/w), respectively. The use of hydrocolloids had no effect on total phenolic contents, antioxidant properties (DPPH, ABTS, and FRAP), color, and X-ray diffraction patterns (p > 0.05). In contrast, the hydrocolloids tended to increase the expansion ration of the noodle. GG and CMC improved cooking, textural, and sensory properties. Ultimately, 0.2%-GG showed the lowest cooking loss (5.07%) when compared with others. Moreover, it also provided the noodle with better textural properties such as tensile strength, extensibility, hardness, cohesiveness, and chewiness (p < 0.05). For these reasons, the highest acceptability (6.75) for the noodle was achieved with GG02. XG resulted in lower overall acceptability (5.05), particularly the 0.4%-XG recipe (p < 0.05). Thus, usage of 0.2%-GG was the best option for improving the qualities of extruded RJF noodle. XG was deemed ineffective for improving the noodle.
Kraithong et al. (2020) Effects of food hydrocolloids on quality attributes of extruded red Jasmine rice noodle. PeerJ 8:e10235 https://doi.org/10.7717/peerj.10235