Isolation and characterization of a motility-defective mutant of Euglena gracilis
Euglena gracilis is a green photosynthetic microalga that swims using its flagellum. This species has been used as a model organism for over half a century to study its metabolism and the mechanisms of its behavior. The development of mass-cultivation technology has led to E. gracilis application as a feedstock in various products such as foods. Therefore, breeding of E. gracilis has been attempted to improve the productivity of this feedstock for potential industrial applications. For this purpose, a characteristic that preserves the microalgal energy e.g., reduces motility, should be added to the cultivars. The objective of this study was to verify our hypothesis that E. gracilis locomotion-defective mutants are suitable for industrial applications because they save the energy required for locomotion. To test this hypothesis, we screened for E. gracilis mutants from Fe-ion-irradiated cell suspensions and established a mutant strain, ${\mathrm{M}}_{3}^{-}$ M 3 − ZFeL, which shows defects in flagellum formation and locomotion. The mutant strain exhibits a growth rate comparable to that of the wild type when cultured under autotrophic conditions, but had a slightly slower growth under heterotrophic conditions. It also stores 1.6 times the amount of paramylon, a crystal of β-1,3-glucan, under autotrophic culture conditions, and shows a faster sedimentation compared with that of the wild type, because of the deficiency in mobility and probably the high amount of paramylon accumulation. Such characteristics make E. gracilis mutant cells suitable for cost-effective mass cultivation and harvesting.
Muramatsu et al. (2020) Isolation and characterization of a motility-defective mutant of Euglena gracilis. PeerJ 8:e10002 https://doi.org/10.7717/peerj.10002
Differing physiological and behavioral responses to anthropogenic factors between resident and non-resident African elephants at Mpala Ranch, Laikipia County, Kenya
Background Heterogeneous landscapes like those of Laikipia County, Kenya consist of a mosaic of land-use types, which may exert differential physiological effects on elephants that occupy and traverse them. Understanding behavioral and physiological states of wild African elephants in response to the challenges of living in human-dominated landscapes is therefore important for conservation managers to evaluate risks imposed by elephants to humans and vice versa. Several conservation physiology tools have been developed to assess how animals respond to both natural and anthropogenic changes, and determine biological impacts. This study investigated how migratory and avoidance behavioral to vehicle presence, and vegetation quality affected fecal glucocorticoid (GC) metabolite (FGM) concentrations in African elephants at Mpala Ranch, Laikipia County, Kenya. Methods The study compared adrenal glucocorticoid activity of resident elephants that live within Mpala (n = 57) and non-resident elephants whose space use patterns overlap several ranches (n = 99) in Laikipia County, Kenya. Fecal samples were collected for a 4-month period between April and August for analysis of FGM concentrations. Behavioral reactions to research vehicles and body condition also were assessed. Satellite images from Terra Moderate Resolution Imaging (MODIS MOD13Q1) were downloaded and processed using Google Earth Engine to calculate a Normalized Difference Vegetation Index (NDVI) as a measure of vegetation quality. Results As expected, there was a positive correlation between avoidance behavior to vehicle presence and FGM concentrations in both resident and non-resident elephants, whereas there was an inverse relationship between FGM concentrations and NDVI values. Our study also found a positive influence of age on the FGM concentrations, but there were no relationships between FGM and sex, social group type, herd size, and body condition. However, contrary to our expectations, resident elephants had higher FGM concentrations than non-residents. Discussion Findings reveal elephants with stronger avoidance responses to research vehicles and resident elephants with relatively smaller home ranges exhibited higher FGM concentrations within the Mpala Ranch, Kenya and surrounding areas. Higher vegetative quality within the ranges occupied by non-resident elephants in Laikipia may be one reason for lower FGM, and an indication that the non-residents are tracking better forage quality to improve energy balance and reduce overall GC output. Additionally, our study found a positive influence of age, but no other demographic variables on FGM concentrations. Finally, adrenal glucocorticoid activity was inversely related to vegetative quality. Our findings can help conservation managers better understand how behavior and environment influences the physiological states of African elephants, and how management intervention might mitigate negative human–elephant interactions.
Oduor et al. (2020) Differing physiological and behavioral responses to anthropogenic factors between resident and non-resident African elephants at Mpala Ranch, Laikipia County, Kenya. PeerJ 8:e10010 https://doi.org/10.7717/peerj.10010
Pyruvate is required for catecholamine-stimulated growth of different strains of Campylobacter jejuni
Humans and food-producing animals are constantly exposed to and affected by stress. As a consequence of stress, the release of stress-related catecholamines, such as norepinephrine (NE) and dopamine (DA), from nerve terminals in the gastrointestinal tract potentiates both the growth and the virulence of pathogenic bacteria. This may lead to the enhancement of gastrointestinal infections in humans or food-producing animals. Compared with foodborne bacterial pathogens such as Escherichia coli and Salmonella spp., less is known about the effect of stress catecholamines on Campylobacter jejuni subsp. jejuni. The present study focuses on the effect(s) of stress catecholamines DA and NE in iron-restricted media and how they affect the growth of different C. jejuni strains NCTC 11168, 81–176, and ML2126. Results demonstrated that DA- and NE-enhanced growth of C. jejuni in iron-restricted media may involve different mechanisms that cannot be explained by current understanding which relies on catecholamine-mediated iron delivery. Specifically, we found that DA-enhanced growth requires pyruvate, whereas NE-enhanced growth does not. We further report significant strain-specific dependence of C. jejuni growth on various catecholamines in the presence or absence of pyruvate. These data provide novel insights into the effect(s) of stress catecholamines on the in vitro growth of C. jejuni in iron-restricted environments, such as the intestinal tract. They suggest a mechanism by which stress-related catecholamines affect the growth of C. jejuni in the intestinal tract of food-producing animals, which in turn may influence colonization and transmission to humans.
Liu et al. (2020) Pyruvate is required for catecholamine-stimulated growth of different strains of Campylobacter jejuni. PeerJ 8:e10011 https://doi.org/10.7717/peerj.10011
The utility of MEWS for predicting the mortality in the elderly adults with COVID-19: a retrospective cohort study with comparison to other predictive clinical scores
Background Older adults have been reported to be a population with high-risk of death in the COVID-19 outbreak. Rapid detection of high-risk patients is crucial to reduce mortality in this population. The aim of this study was to evaluate the prognositc accuracy of the Modified Early Warning Score (MEWS) for in-hospital mortality in older adults with COVID-19. Methods A retrospective cohort study was conducted in Wuhan Hankou Hospital in China from 1 January 2020 to 29 February 2020. Receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of MEWS, Acute Physiology and Chronic Health Evaluation II (APACHE II), Sequential Organ Function Assessment (SOFA), quick Sequential Organ Function Assessment (qSOFA), Pneumonia Severity Index (PSI), Combination of Confusion, Urea, Respiratory Rate, Blood Pressure, and Age ≥65 (CURB-65), and the Systemic Inflammatory Response Syndrome Criteria (SIRS) for in-hospital mortality. Logistic regression models were performed to detect the high-risk older adults with COVID-19. Results Among the 235 patients included in this study, 37 (15.74%) died and 131 (55.74%) were male, with an average age of 70.61 years (SD 8.02). ROC analysis suggested that the capacity of MEWS in predicting in-hospital mortality was as good as the APACHE II, SOFA, PSI and qSOFA (Difference in AUROC: MEWS vs. APACHE II, −0.025 (95% CI [−0.075 to 0.026]); MEWS vs. SOFA, −0.013 (95% CI [−0.049 to 0.024]); MEWS vs. PSI, −0.015 (95% CI [−0.065 to 0.035]); MEWS vs. qSOFA, 0.024 (95% CI [−0.029 to 0.076]), all P > 0.05), but was significantly higher than SIRS and CURB-65 (Difference in AUROC: MEWS vs. SIRS, 0.218 (95% CI [0.156–0.279]); MEWS vs. CURB-65, 0.064 (95% CI [0.002–0.125]), all P < 0.05). Logistic regression models implied that the male patients (≥75 years) had higher risk of death than the other older adults (estimated coefficients: 1.16, P = 0.044). Our analysis further suggests that the cut-off points of the MEWS score for the male patients (≥75 years) subpopulation and the other elderly patients should be 2.5 and 3.5, respectively. Conclusions MEWS is an efficient tool for rapid assessment of elderly COVID-19 patients. MEWS has promising performance in predicting in-hospital mortality and identifying the high-risk group in elderly patients with COVID-19.
Wang et al. (2020) The utility of MEWS for predicting the mortality in the elderly adults with COVID-19: a retrospective cohort study with comparison to other predictive clinical scores. PeerJ 8:e10018 https://doi.org/10.7717/peerj.10018
Predicting CoVID-19 community mortality risk using machine learning and development of an online prognostic tool
Background The recent pandemic of CoVID-19 has emerged as a threat to global health security. There are very few prognostic models on CoVID-19 using machine learning. Objectives To predict mortality among confirmed CoVID-19 patients in South Korea using machine learning and deploy the best performing algorithm as an open-source online prediction tool for decision-making. Materials and Methods Mortality for confirmed CoVID-19 patients (n = 3,524) between January 20, 2020 and May 30, 2020 was predicted using five machine learning algorithms (logistic regression, support vector machine, K nearest neighbor, random forest and gradient boosting). The performance of the algorithms was compared, and the best performing algorithm was deployed as an online prediction tool. Results The logistic regression algorithm was the best performer in terms of discrimination (area under ROC curve = 0.830), calibration (Matthews Correlation Coefficient = 0.433; Brier Score = 0.036) and. The best performing algorithm (logistic regression) was deployed as the online CoVID-19 Community Mortality Risk Prediction tool named CoCoMoRP (https://ashis-das.shinyapps.io/CoCoMoRP/). Conclusions We describe the development and deployment of an open-source machine learning tool to predict mortality risk among CoVID-19 confirmed patients using publicly available surveillance data. This tool can be utilized by potential stakeholders such as health providers and policymakers to triage patients at the community level in addition to other approaches.
Das et al. (2020) Predicting CoVID-19 community mortality risk using machine learning and development of an online prognostic tool. PeerJ 8:e10083 https://doi.org/10.7717/peerj.10083
Suitability of native milkweed (Asclepias) species versus cultivars for supporting monarch butterflies and bees in urban gardens
Public interest in ecological landscaping and gardening is fueling a robust market for native plants. Most plants available to consumers through the horticulture trade are cultivated forms that have been selected for modified flowers or foliage, compactness, or other ornamental characteristics. Depending on their traits, some native plant cultivars seem to support pollinators, specialist insect folivores, and insect-based vertebrate food webs as effectively as native plant species, whereas others do not. There is particular need for information on whether native cultivars can be as effective as true or “wild-type” native species for supporting specialist native insects of conservation concern. Herein we compared the suitability of native milkweed species and their cultivars for attracting and supporting one such insect, the iconic monarch butterfly (Danaus plexippus L.), as well as native bees in urban pollinator gardens. Wild-type Asclepias incarnata L. (swamp milkweed) and Asclepias tuberosa L. (butterfly milkweed) and three additional cultivars of each that vary in stature, floral display, and foliage color were grown in a replicated common garden experiment at a public arboretum. We monitored the plants for colonization by wild monarchs, assessed their suitability for supporting monarch larvae in greenhouse trials, measured their defensive characteristics (leaf trichome density, latex, and cardenolide levels), and compared the proportionate abundance and diversity of bee families and genera visiting their blooms. Significantly more monarch eggs and larvae were found on A. incarnata than A. tuberosa in both years, but within each milkweed group, cultivars were colonized to the same extent as wild types. Despite some differences in defense allocation, all cultivars were as suitable as wild-type milkweeds in supporting monarch larval growth. Five bee families and 17 genera were represented amongst the 2,436 total bees sampled from blooms of wild-type milkweeds and their cultivars in the replicated gardens. Bee assemblages of A. incarnata were dominated by Apidae (Bombus, Xylocopa spp., and Apis mellifera), whereas A. tuberosa attracted relatively more Halictidae (especially Lasioglossum spp.) and Megachilidae. Proportionate abundance of bee families and genera was generally similar for cultivars and their respective wild types. This study suggests that, at least in small urban gardens, milkweed cultivars can be as suitable as their parental species for supporting monarch butterflies and native bees.
Baker et al. (2020) Suitability of native milkweed (Asclepias) species versus cultivars for supporting monarch butterflies and bees in urban gardens. PeerJ 8:e9823 https://doi.org/10.7717/peerj.9823
Dung beetle species introductions: when an ecosystem service provider transforms into an invasive species
Dung beetle introduction programmes were designed to accelerate exotic livestock dung degradation and to control dung breeding pestiferous flies and livestock parasites. The introduction programmes provided exotic dung beetle species with an opportunity to cross natural barriers and spread beyond their native range. There are no reports that explain what probable adaptation mechanisms enable particular dung beetle species to be the most successful invader. Here we identify the morphological, biological, physiological, ecological and behavioural attributes of the four most widespread and successful dung beetle species in introduced areas on a global scale in relation to the assumption that these species are different from other exotic and native dung beetles. We have recognised Digitonthophagus gazella (Fabricius), Onthophagus taurus (Schreber), Euoniticellus intermedius (Reiche) and Aphodius fimetarius (Linnaeus) as the most successful invaders based on their spread, predominance, distribution range and the reports of invasion. Each of these four species has different natural history traits that increase their fitness making them successful invaders. D. gazella has high fecundity and spreading ability, can instantly locate and colonise fresh and nutritious dung, and has a broad thermal window. O. taurus has morphological plasticity, high fecundity, high brood survival rate due to bi-parenting, and is adapted to extreme thermal and moisture conditions. E. intermedius has remnant-dung feeding abilities, a wide thermal window, functioning best at upper-temperature levels, and successful breeding and survival abilities at extremely low soil moisture conditions. A. fimetarius is small-sized, has high breeding and dispersal abilities, and is adapted to lower thermal and upper moisture extremes and variable soil conditions. Discussed here are perspectives on adaptive attributes of dung beetle species that are important to consider during their selection for redistributions. We have elaborated on the fitness and success characteristics of the four species individually. Further, we recommend a prior-introduction baseline monitoring of native dung beetle assemblages so as to evaluate the future impact of exotic dung beetle introductions on the recipient ecosystem.
Pokhrel et al. (2020) Dung beetle species introductions: when an ecosystem service provider transforms into an invasive species. PeerJ 8:e9872 https://doi.org/10.7717/peerj.9872
Exploring the role of individual learning in animal tool-use
The notion that tool-use is unique to humans has long been refuted by the growing number of observations of animals using tools across various contexts. Yet, the mechanisms behind the emergence and sustenance of these tool-use repertoires are still heavily debated. We argue that the current animal behaviour literature is biased towards a social learning approach, in which animal, and in particular primate, tool-use repertoires are thought to require social learning mechanisms (copying variants of social learning are most often invoked). However, concrete evidence for a widespread dependency on social learning is still lacking. On the other hand, a growing body of observational and experimental data demonstrates that various animal species are capable of acquiring the forms of their tool-use behaviours via individual learning, with (non-copying) social learning regulating the frequencies of the behavioural forms within (and, indirectly, between) groups. As a first outline of the extent of the role of individual learning in animal tool-use, a literature review of reports of the spontaneous acquisition of animal tool-use behaviours was carried out across observational and experimental studies. The results of this review suggest that perhaps due to the pervasive focus on social learning in the literature, accounts of the individual learning of tool-use forms by naïve animals may have been largely overlooked, and their importance under-examined.
Bandini et al. (2020) Exploring the role of individual learning in animal tool-use. PeerJ 8:e9877 https://doi.org/10.7717/peerj.9877
Genome-wide analysis of PRR gene family uncovers their roles in circadian rhythmic changes and response to drought stress in Gossypium hirsutum L.
Background The circadian clock not only participates in regulating various stages of plant growth, development and metabolism, but confers plant environmental adaptability to stress such as drought. Pseudo-Response Regulators (PRRs) are important component of the central oscillator (the core of circadian clock) and play a significant role in plant photoperiod pathway. However, no systematical study about this gene family has been performed in cotton. Methods PRR genes were identified in diploid and tetraploid cotton using bioinformatics methods to investigate their homology, duplication and evolution relationship. Differential gene expression, KEGG enrichment analysis and qRT-PCR were conducted to analyze PRR gene expression patterns under diurnal changes and their response to drought stress. Results A total of 44 PRR family members were identified in four Gossypium species, with 16 in G. hirsutum, 10 in G. raimondii, and nine in G. barbadense as well as in G. arboreum. Phylogenetic analysis indicated that PRR proteins were divided into five subfamilies and whole genome duplication or segmental duplication contributed to the expansion of Gossypium PRR gene family. Gene structure analysis revealed that members in the same clade are similar, and multiple cis-elements related to light and drought stress response were enriched in the promoters of GhPRR genes. qRT-PCR results showed that GhPRR genes transcripts presented four expression peaks (6 h, 9 h, 12 h, 15 h) during 24 h and form obvious rhythmic expression trend. Transcriptome data with PEG treatment, along with qRT-PCR verification suggested that members of clade III (GhPRR5a, b, d) and clade V (GhPRR3a and GhPRR3c) may be involved in drought response. This study provides an insight into understanding the function of PRR genes in circadian rhythm and in response to drought stress in cotton.
Wang et al. (2020) Genome-wide analysis of PRR gene family uncovers their roles in circadian rhythmic changes and response to drought stress in Gossypium hirsutum L.. PeerJ 8:e9936 https://doi.org/10.7717/peerj.9936
Analysis of the infant gut microbiome reveals metabolic functional roles associated with healthy infants and infants with atopic dermatitis using metaproteomics
The infant gut microbiome consists of a complex and diverse microbial community. Comprehensive taxonomic and metabolic functional knowledge about microbial communities supports medical and biological applications, such as fecal diagnostics. Among the omics approaches available for the investigation of microbial communities, metaproteomics-based analysis is a very powerful approach; under this method, the activity of microbial communities is explored by investigating protein expression within a sample. Through use of metaproteomics, this study aimed to investigate the microbial community composition of the infant gut to identify different key proteins playing metabolic functional roles in the microbiome of healthy infants and infants with atopic dermatitis in a Thai population-based birth cohort. Here, 18 fecal samples were analyzed by liquid chromatography-tandem mass spectrometry to conduct taxonomic, functional, and pathway-based protein annotation. Accordingly, 49,973 annotated proteins out of 68,232 total proteins were investigated in gut microbiome samples and compared between the healthy and atopic dermatitis groups. Through differentially expressed proteins (DEPs) analysis, 130 significant DEPs were identified between the healthy and atopic dermatitis groups. Among these DEPs, eight significant proteins were uniquely expressed in the atopic dermatitis group. For instance, triosephosphate isomerase (TPI) in Bifidobacteriaceae in the genus Alloscardovia and demethylmenaquinone methyltransferase (DMM) in Bacteroides were shown to potentially play metabolic functional roles related to disease. PPI network analysis revealed seven reporter proteins showing metabolic alterations between the healthy and disease groups associated with the biosynthesis of ubiquinone and other quinones as well as the energy supply. This study serves as a scaffold for microbial community-wide metabolic functional studies of the infant gut microbiome in relation to allergic disease.
Kingkaw et al. (2020) Analysis of the infant gut microbiome reveals metabolic functional roles associated with healthy infants and infants with atopic dermatitis using metaproteomics. PeerJ 8:e9988 https://doi.org/10.7717/peerj.9988