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Quinoa (Chenopodium quinoa Willd.) is an herbaceous annual crop of the amaranth family (Amaranthaceae). It is increasingly cultivated for its nutritious grains, which are rich in protein and essential amino acids, lipids, and minerals. Quinoa exhibits a high tolerance towards various abiotic stresses including drought and salinity, which supports its agricultural cultivation under climate change conditions. The use of quinoa grains is compromised by anti-nutritional saponins, a terpenoid class of secondary metabolites deposited in the seed coat; their removal before consumption requires extensive washing, an economically and environmentally unfavorable process; or their accumulation can be reduced through breeding. In this study, we analyzed the seed metabolomes, including amino acids, fatty acids, and saponins, from 471 quinoa cultivars, including two related species, by liquid chromatography - mass spectrometry. Additionally, we determined a large number of agronomic traits including biomass, flowering time, and seed yield. The results revealed considerable diversity between genotypes and provide a knowledge base for future breeding or genome editing of quinoa.
In plants, the trehalose biosynthetic pathway plays key roles in the regulation of carbon allocation and stress adaptation.
Engineering of the pathway holds great promise to increase the stress resilience of crop plants.
The synthesis of trehalose proceeds by a two-step pathway in which a trehalose-phosphate synthase (TPS) uses UDP-glucose and glucose-6-phosphate to produce trehalose-6 phosphate (T6P) that is subsequently dephosphorylated by trehalose-6 phosphate phosphatase (TPP).
While plants usually do not accumulate high amounts of trehalose, their genome encodes large families of putative trehalose biosynthesis genes, with many members lacking obvious enzymatic activity.
Thus, the function of putative trehalose biosynthetic proteins in plants is only vaguely understood. To gain a deeper insight into the role of trehalose biosynthetic proteins in crops, we assessed the enzymatic activity of the TPS/TPP family from tomato (Solanum lycopersicum L.) and investigated their expression pattern in different tissues as well as in response to temperature shifts. From the 10 TPS isoforms tested, only the 2 proteins belonging to class I showed enzymatic activity, while all 5 TPP isoforms investigated were catalytically active.
Most of the TPS/TPP family members showed the highest expression in mature leaves, and promoter-reporter gene studies suggest that the two class I TPS genes have largely overlapping expression patterns within the vasculature, with only subtle differences in expression in fruits and flowers.
The majority of tomato TPS/TPP genes were induced by heat stress, and individual family members also responded to cold.
This suggests that trehalose biosynthetic pathway genes could play an important role during temperature stress adaptation.
In summary, our study represents a further step toward the exploitation of the TPS and TPP gene families for the improvement of tomato stress resistance.
Cell division and the resulting changes to the cell organization affect the shape and functionality of all tissues.
Thus, understanding the determinants of the tissue-wide changes imposed by cell division is a key question in developmental biology.
Here, we use a network representation of live cell imaging data from shoot apical meristems (SAMs) in Arabidopsis thaliana to predict cell division events and their consequences at the tissue level.
We show that a support vector machine classifier based on the SAM network properties is predictive of cell division events, with test accuracy of 76%, which matches that based on cell size alone.
Furthermore, we demonstrate that the combination of topological and biological properties, including cell size, perimeter, distance and shared cell wall between cells, can further boost the prediction accuracy of resulting changes in topology triggered by cell division.
Using our classifiers, we demonstrate the importance of microtubule-mediated cell-to-cell growth coordination in influencing tissue-level topology.
Together, the results from our network-based analysis demonstrate a feedback mechanism between tissue topology and cell division in A. thaliana SAMs.
Oil palm (Elaeis guineensis Jacq.) is the most productive oil-producing crop per hectare of land. The oil that accumulates in the mesocarp tissue of the fruit is the highest observed among fruit-producing plants. A comparative analysis between high-, medium-, and low-yielding oil palms, particularly during fruit development, revealed unique characteristics. Metabolomics analysis was able to distinguish accumulation patterns defining of the various developmental stages and oil yield. Interestingly, high- and medium-yielding oil palms exhibited substantially increased sucrose levels compared to low-yielding palms. In addition, parameters such as starch granule morphology, granule size, total starch content, and starch chain length distribution (CLD) differed significantly among the oil yield categories with a clear correlation between oil yield and various starch parameters. These results provide new insights into carbohydrate and starch metabolism for biosynthesis of oil palm fruits, indicating that starch and sucrose can be used as novel, easy-to-analyze, and reliable biomarker for oil yield.
Current evidence suggests that migratory animals extract map information from the geomagnetic field for true navigation. The sensory basis underlying this feat is elusive, but presumably involves magnetic particles.
A common experimental manipulation procedure consists of pre-treating animals with a magnetic pulse, with the aim of re-magnetising particles to alter the internal representation of the external field prior to a navigation task.
Although pulsing provoked deflected bearings in caged songbirds, analogous studies with free-flying songbirds yielded inconsistent results.
Here, we pulsed European robins (Erithacus rubecula) at an offshore stopover site during spring migration and monitored their free-flight behaviour with a regional-scale network of radio-receiving stations.
We found no pulse effect on departure probability, nocturnal departure timing departure direction or consistency of flight direction.
This suggests either no use of the geomagnetic map by our birds, or that magnetic pulses do not affect the sensory system underlying geomagnetic map detection.
Ciliates represent a crucial link between phytoplankton and bacteria and mesozooplankton in pelagic food webs, but little is known about the processes influencing the dynamics of individual species.
Using long-term, high-frequency observations, we compared the diversity and the temporal variability in biomass and species composition of the ciliate community in large, deep, mesotrophic Lake Constance to that of the phytoplankton and rotifer communities in the same lake.
Furthermore, we used boosted regression trees to evaluate possible environmental predictors (temperature, three prey groups, four predator/competitor groups) influencing ciliate net growth.
The biomass of all ciliate species showed a common, recurrent seasonal pattern, often with peaks in spring and summer.
The ciliate community was more diverse than the rotifer community, exhibited highly synchronous dynamics and its species were regularly encountered during the season. The top-down control by copepods likely contributes to the ciliates' synchronized decline prior to the clear-water phase when food concentration is still high.
The high temporal autocorrelation of the ciliate biomasses together with the inter-annual recurrent seasonal patterns and the low explanatory power of the environmental predictors suggest that the dynamics of individual ciliate species are strictly controlled, yet it remains difficult to determine the responsible factors.
Volatile organic compounds (VOCs) are involved in microbial interspecies communication and in the mode of action of various antagonistic interactions. They are important for balancing host-microbe interactions and provide the basis for developing biological control strategies to control plant pathogens.
We studied the interactions between the bacterial antagonist Serratia plymuthica HRO-C48 and three fungal plant pathogens Rhizoctonia solani, Leptosphaeria maculans and Verticillium longisporum. Significant differences in fungal growth inhibition by the Serratia-emitted VOCs in pairwise dual culture assays and changes in the transcriptome of the bacterium and in the volatilomes of both interacting partners were observed. Even though the rate of fungal growth inhibition by Serratia was variable, the confrontation of the bacterium with the VOCs of all three fungi changed the levels of expression of the genes involved in stress response, biofilm formation, and the production of antimicrobial VOCs. Pairwise interacting microorganisms switched between defense (downregulation of gene expression) and attack (upregulation of gene expression and metabolism followed by growth inhibition of the interacting partner) modes, subject to the combinations of microorganisms that were interacting.
In the attack mode HRO-C48 significantly inhibited the growth of R. solani while simultaneously boosting its own metabolism; by contrast, its metabolism was downregulated when HRO-C48 went into a defense mode that was induced by the L. maculans and V. longisporum VOCs. L. maculans growth was slightly reduced by the one bacterial VOC methyl acetate that induced a strong downregulation of expression of genes involved in almost all metabolic functions in S. plymuthica.
Similarly, the interaction between S. plymuthica and V. longisporum resulted in an insignificant growth reduction of the fungus and repressed the rate of bacterial metabolism on the transcriptional level, accompanied by an intense volatile dialogue. Overall, our results indicate that VOCs substantially contribute to the highly break species-specific interactions between pathogens and their natural antagonists and thus deserving of increased consideration for pathogen control.
Quantifying the influence of pollen aging on the adhesive
properties of Hypochaeris radicata pollen
(2022)
Simple Summary Pollination is the transfer of pollen from a plant's male part (anther) to the corresponding female part (stigma). It is a fundamental biological process that ensures plant reproduction. Most studies investigate pollination from a biological perspective, but the underlying physical processes are poorly understood. Many plants rely on insects to transport pollen and the forces with which pollen adhere to insects and floral surfaces are fundamental for successful pollination.
We quantified pollen adhesion by measuring the forces necessary to detach Hypochaeris radicata (catsear, a common insect-pollinated plant) pollen from glass and studied for the first time how the adhesion forces change with pollen aging.
Our results show that newly formed adhesion bonds between H. radicata pollen and glass are stronger for fresh pollen than for old ones. On the other hand, when H. radicata pollen age in contact with glass, the adhesion between pollen and glass strengthens over time. These effects are probably caused by the viscous liquid covering most pollen (pollenkitt) changing its viscoelastic properties as it dries.
Although pollination is one of the most crucial biological processes that ensures plant reproduction, its mechanisms are poorly understood. Especially in insect-mediated pollination, a pollen undergoes several attachment and detachment cycles when being transferred from anther to insect and from insect to stigma. The influence of the properties of pollen, insect and floral surfaces on the adhesion forces that mediate pollen transfer have been poorly studied.
Here, we investigate the adhesive properties of Hypochaeris radicata pollen and their dependence on pollen aging by quantifying the pull-off forces from glass slides using centrifugation and atomic force microscopy. We found that the properties of the pollenkitt-the viscous, lipid liquid on the surface of most pollen grains-influences the forces necessary to detach a pollen from hydrophilic surfaces.
Our results show that aged H. radicata pollen form weaker adhesions to hydrophilic glass than fresh ones. On the other hand, when a pollen grain ages in contact with glass, the adhesion between the two surfaces increases over time.
This study shows for the first time the pollen aging effect on the pollination mechanism.
Background
Long-term selection experiments are a powerful tool to understand the genetic background of complex traits. The longest of such experiments has been conducted in the Research Institute for Farm Animal Biology (FBN), generating extreme mouse lines with increased fertility, body mass, protein mass and endurance. For >140 generations, these lines have been maintained alongside an unselected control line, representing a valuable resource for understanding the genetic basis of polygenic traits. However, their history and genomes have not been reported in a comprehensive manner yet. Therefore, the aim of this study is to provide a summary of the breeding history and phenotypic traits of these lines along with their genomic characteristics. We further attempt to decipher the effects of the observed line-specific patterns of genetic variation on each of the selected traits.
Results
Over the course of >140 generations, selection on the control line has given rise to two extremely fertile lines (>20 pups per litter each), two giant growth lines (one lean, one obese) and one long-distance running line. Whole genome sequencing analysis on 25 animals per line revealed line-specific patterns of genetic variation among lines, as well as high levels of homozygosity within lines. This high degree of distinctiveness results from the combined effects of long-term continuous selection, genetic drift, population bottleneck and isolation. Detection of line-specific patterns of genetic differentiation and structural variation revealed multiple candidate genes behind the improvement of the selected traits.
Conclusions
The genomes of the Dummerstorf trait-selected mouse lines display distinct patterns of genomic variation harbouring multiple trait-relevant genes. Low levels of within-line genetic diversity indicate that many of the beneficial alleles have arrived to fixation alongside with neutral alleles. This study represents the first step in deciphering the influence of selection and neutral evolutionary forces on the genomes of these extreme mouse lines and depicts the genetic complexity underlying polygenic traits.
Plant cell walls are versatile materials that can adopt a wide range of mechanical properties through controlled deposition of cellulose fibrils. Wall integrity requires a sufficiently homogeneous fibril distribution to cope effectively with wall stresses. Additionally, specific conditions, such as the negative pressure in water transporting xylem vessels, may require more complex wall patterns, e.g., bands in protoxylem.
The orientation and patterning of cellulose fibrils are guided by dynamic cortical microtubules.
New microtubules are predominantly nucleated from parent microtubules causing positive feedback on local microtubule density with the potential to yield highly inhomogeneous patterns. Inhomogeneity indeed appears in all current cortical array simulations that include microtubule-based nucleation, suggesting that plant cells must possess an as-yet unknown balancing mechanism to prevent it.
Here, in a combined simulation and experimental approach, we show that a limited local recruitment of nucleation complexes to microtubules can counter the positive feedback, whereas local tubulin depletion cannot.
We observe that nucleation complexes preferentially appear at the plasma membrane near microtubules. By incorporating our experimental findings in stochastic simulations, we find that the spatial behavior of nucleation complexes delicately balances the positive feedback, such that differences in local microtubule dynamics-as in developing protoxylem-can quickly turn a homogeneous array into a banded one. Our results provide insight into how the plant cytoskeleton has evolved to meet diverse mechanical requirements and greatly increase the predictive power of computational cell biology studies.
Paleogenomes reveal a complex evolutionary history of late Pleistocene bison in Northeastern China
(2022)
Steppe bison are a typical representative of the Mid-Late Pleistocene steppes of the northern hemisphere.
Despite the abundance of fossil remains, many questions related to their genetic diversity, population structure and dispersal route are still elusive.
Here, we present both near-complete and partial mitochondrial genomes, as well as a partial nuclear genome from fossil bison samples excavated from Late Pleistocene strata in northeastern China.
Maximum-likelihood and Bayesian trees both suggest the bison clade are divided into three maternal haplogroups (A, B and C), and Chinese individuals fall in two of them. Bayesian analysis shows that the split between haplogroup C and the ancestor of haplogroups A and B dates at 326 ky BP (95% HPD: 397-264 ky BP).
In addition, our nuclear phylogenomic tree also supports a basal position for the individual carrying haplogroup C. Admixture analyses suggest that CADG467 (haplogroup C) has a similar genetic structure to steppe bison from Siberia (haplogroup B).
Our new findings indicate that the genetic diversity of Pleistocene bison was probably even higher than previously thought and that northeastern Chinese populations of several mammalian species, including Pleistocene bison, were genetically distinct.
Meropenem is one of the most frequently used antibiotics to treat life-threatening infections in critically ill patients.
This study aimed to develop a meropenem dosing algorithm for the treatment of Gram-negative infections based on intensive care unit (ICU)-specific resistance data. Antimicrobial susceptibility testing of Gram-negative bacteria obtained from critically ill patients was carried out from 2016 to 2020 at a tertiary care hospital.
Based on the observed MIC distribution, stochastic simulations (n = 1,000) of an evaluated pharmacokinetic meropenem model, and a defined pharmacokinetic/pharmacodynamic target (100%T->4xMIC while minimum concentrations were <44.5 mg/L), dosing recommendations for patients with varying renal function were derived.
Pathogen-specific MIC distributions were used to calculate the cumulative fraction of response (CFR), and the overall MIC distribution was used to calculate the local pathogen-independent mean fraction of response (LPIFR) for the investigated dosing regimens.
A CFR/LPIFR of >90% was considered adequate. The observed MIC distribution significantly differed from the EUCAST database. Based on the 6,520 MIC values included, a three-level dosing algorithm was developed.
If the pathogen causing the infection is unknown (level 1), known (level 2), known to be neither Pseudomonas aeruginosa nor Acinetobacrer baumannii, or classified as susceptible (level 3), a continuous infusion of 1.5 g daily reached sufficient target attainment independent of renal function.
In all other cases, dosing needs to be adjusted based on renal function. ICU-specific susceptibility data should be assessed regularly and integrated into dosing decisions. The presented workflow may serve as a blueprint for other antimicrobial settings.
During a survey of aquatic fungi from Anzali Lagoon in Iran, several fungal specimens were isolated from freshwater habitats. Morphological evidence and comparing sequencing based on rDNA (ITS and LSU) and protein-coding genes (TEF1 and TUB2) showed that some isolates belong to undescribed fungal species.
These isolates belong to Arthrobotrys and Sarocladium, two ascomycetes genera. Arthrobotrys hyrcanus, sp. nov., differs from closely related species such as A. dianchiensis by its larger conidia and septation of primary conidia. Sarocladium pseudokiliense, sp. nov., was similar to S. kiliense, but distinguished by its conidial shape and the absence of adelophialides and chlamydospores.
Morphological descriptions, illustrations and multilocus phylogenetic analysis for both new species are provided.
Riverine ecosystems provide various ecosystem services. One of these services is the biological control of eutrophication by grazing macroinvertebrates.
However, riverine ecosystems are subject to numerous stressors that affect community structure, functions, and stability properties. To manage rivers in response to these stressors, a better understanding of the ecological functions underlying services is needed.
This requires consideration of local and regional processes, which requires a metacommunity approach that links local food webs through drift and dispersal. This takes into account long-distance interactions that can compensate for local effects of stressors.
Our modular model MASTIFF (Multiple Aquatic STressors In Flowing Food webs) is stage-structured, spatially explicit, and includes coupled food webs consisting of benthic resource-consumer interactions between biofilm and three competing macroinvertebrate functional types. River segments are unidirectionally connected through organismal drift and bidirectionally connected through dispersal. Climate and land use stressors along the river can be accounted for. Biocontrol of biofilm eutrophication is used as an exemplary functional indicator.
We present the model and the underlying considerations, and show in an exemplary application that explicit consideration of drift and dispersal is essential for understanding the spatiotemporal biocontrol of eutrophication.
The combination of drift and dispersal reduced eutrophication events. While dispersal events were linked to specific periods in the species life cycles and therefore had limited potential to control, drift was ubiquitous and thus responded more readily to changing habitat conditions.
This indicates that drift is an important factor for coping with stress situations.
Finally, we outline and discuss the potential and possibilities of MASTIFF as a tool for mechanistic, cross-scale analyses of multiple stressors to advance knowledge of riverine ecosystem functioning.
Sulfur is an important element that is incorporated into many biomolecules in humans. The incorporation and transfer of sulfur into biomolecules is, however, facilitated by a series of different sulfurtransferases. Among these sulfurtransferases is the human mercaptopyruvate sulfurtransferase (MPST) also designated as tRNA thiouridine modification protein (TUM1). The role of the human TUM1 protein has been suggested in a wide range of physiological processes in the cell among which are but not limited to involvement in Molybdenum cofactor (Moco) biosynthesis, cytosolic tRNA thiolation and generation of H2S as signaling molecule both in mitochondria and the cytosol. Previous interaction studies showed that TUM1 interacts with the L-cysteine desulfurase NFS1 and the Molybdenum cofactor biosynthesis protein 3 (MOCS3). Here, we show the roles of TUM1 in human cells using CRISPR/Cas9 genetically modified Human Embryonic Kidney cells. Here, we show that TUM1 is involved in the sulfur transfer for Molybdenum cofactor synthesis and tRNA thiomodification by spectrophotometric measurement of the activity of sulfite oxidase and liquid chromatography quantification of the level of sulfur-modified tRNA. Further, we show that TUM1 has a role in hydrogen sulfide production and cellular bioenergetics.
In late summer, migratory bats of the temperate zone face the challenge of accomplishing two energy-demanding tasks almost at the same time: migration and mating. Both require information and involve search efforts, such as localizing prey or finding potential mates. In non-migrating bat species, playback studies showed that listening to vocalizations of other bats, both con-and heterospecifics, may help a recipient bat to find foraging patches and mating sites. However, we are still unaware of the degree to which migrating bats depend on con-or heterospecific vocalizations for identifying potential feeding or mating opportunities during nightly transit flights. Here, we investigated the vocal responses of Nathusius’ pipistrelle bats, Pipistrellus nathusii, to simulated feeding and courtship aggregations at a coastal migration corridor. We presented migrating bats either feeding buzzes or courtship calls of their own or a heterospecific migratory species, the common noctule, Nyctalus noctula. We expected that during migratory transit flights, simulated feeding opportunities would be particularly attractive to bats, as well as simulated mating opportunities which may indicate suitable roosts for a stopover. However, we found that when compared to the natural silence of both pre-and post-playback phases, bats called indifferently during the playback of conspecific feeding sounds, whereas P. nathusii echolocation call activity increased during simulated feeding of N. noctula. In contrast, the call activity of P. nathusii decreased during the playback of conspecific courtship calls, while no response could be detected when heterospecific call types were broadcasted. Our results suggest that while on migratory transits, P. nathusii circumnavigate conspecific mating aggregations, possibly to save time or to reduce the risks associated with social interactions where aggression due to territoriality might be expected. This avoidance behavior could be a result of optimization strategies by P. nathusii when performing long-distance migratory flights, and it could also explain the lack of a response to simulated conspecific feeding. However, the observed increase of activity in response to simulated feeding of N. noctula, suggests that P. nathusii individuals may be eavesdropping on other aerial hawking insectivorous species during migration, especially if these occupy a slightly different foraging niche.
The genetic structure of Bryde's whale (Balaenoptera brydei) on the central and western North Pacific feeding grounds was investigated using a total of 1195 mitochondrial control region sequences and 1182 microsatellite genotypes at 17 loci in specimens collected from three longitudinal areas, 1W (135 degrees E-165 degrees E), 1E (165 degrees E-180 degrees), and 2 (180 degrees-155 degrees W). Genetic diversities were similar among areas and a haplotype network did not show any geographic structure, while an analysis of molecular variance found evidence of genetic structure in this species. Pairwise FST and G'ST estimates and heterogeneity tests attributed this structure to weak but significant differentiation between areas 1W/1E and 2. A Mantel test and a high-resolution analysis of genetic diversity statistics showed a weak spatial cline of genetic differentiation. These findings could be reconciled by two possible stock structure scenarios: (1) a single population with kin-association affecting feeding ground preference and (2) two populations with feeding ground preference for either area 1W or area 2. An estimated dispersal rate between areas 1W and 2 indicates that both scenarios should be considered as a precautionary principle in stock assessments.
Here, we demonstrate the utility of native membrane derived vesicles (nMVs) as tools for expeditious electrophysiological analysis of membrane proteins. We used a cell-free (CF) and a cell-based (CB) approach for preparing protein-enriched nMVs. We utilized the Chinese Hamster Ovary (CHO) lysate-based cell-free protein synthesis (CFPS) system to enrich ER-derived microsomes in the lysate with the primary human cardiac voltage-gated sodium channel 1.5 (hNaV1.5; SCN5A) in 3 h. Subsequently, CB-nMVs were isolated from fractions of nitrogen-cavitated CHO cells overexpressing the hNaV1.5. In an integrative approach, nMVs were micro-transplanted into Xenopus laevis oocytes. CB-nMVs expressed native lidocaine-sensitive hNaV1.5 currents within 24 h; CF-nMVs did not elicit any response. Both the CB- and CF-nMV preparations evoked single-channel activity on the planar lipid bilayer while retaining sensitivity to lidocaine application. Our findings suggest a high usability of the quick-synthesis CF-nMVs and maintenance-free CB-nMVs as ready-to-use tools for in-vitro analysis of electrogenic membrane proteins and large, voltage-gated ion channels.
Im Rahmen des PSI-Projekts wurde eine Lehrveranstaltung konzipiert, die Lehramtsstudierenden einen vertieften Einblick sowohl in den Ablauf von Forschung als auch eine Bearbeitung einer eigenen experimentellen Forschungsaufgabe ermöglichen soll. Anlass waren die Berücksichtigung eines „Wissens über Erkenntnisgewinnung in der Disziplin“ im Modell des „Erweiterten Fachwissens für den schulischen Kontext“ (PSI) sowie Erkenntnisse empirischer Studien, die die Relevanz eigener Forschungserfahrung für das Unterrichten naturwissenschaftlicher Erkenntnisgewinnungsprozesse zeigen. Hier stellen wir eine neue Lehrveranstaltung (4 SWS) vor, die den angehenden Lehrkräften Forschungserfahrung ermöglicht (Seminar und Praktikum). Die Lehrveranstaltung vermittelt Einblicke in Forschung und die „Natur der Naturwissenschaften“, ermöglicht das Durchführen eigener wissenschaftlicher und schulrelevanter Experimente und bietet eine angemessene Reflexion über die verschiedenen Kurselemente. Die Evaluationsergebnisse sind überwiegend positiv, zeigen aber auch, dass für die Studierenden die wahrgenommene Schulrelevanz und die fachdidaktischen Aspekte ein wichtiges Kriterium für die positive Bewertung sind.
Twenty-four scientists met for the annual Auxological conference held at Krobielowice castle, Poland, to discuss the diverse influences of the environment and of social behavior on growth following last year’s focus on growth and public health concerns (Hermanussen et al., 2022b). Growth and final body size exhibit marked plastic responses to ecological conditions. Among the shortest are the pygmoid people of Rampasasa, Flores, Indonesia, who still live under most secluded insular conditions. Genetics and nutrition are usually considered responsible for the poor growth in many parts of this world, but evidence is accumulating on the prominent impact of social embedding on child growth. Secular trends not only in the growth of height, but also in body proportions, accompany the secular changes in the social, economic and political conditions, with major influences on the emotional and educational circumstances under which the children grow up (Bogin, 2021). Aspects of developmental tempo and aspects of sports were discussed, and the impact of migration by the example of women from Bangladesh who grew up in the UK. Child growth was considered in particular from the point of view of strategic adjustments of individual size within the network of its social group. Theoretical considerations on network characteristics were presented and related to the evolutionary conservation of growth regulating hypothalamic neuropeptides that have been shown to link behavior and physical growth in the vertebrate species. New statistical approaches were presented for the evaluation of short term growth measurements that permit monitoring child growth at intervals of a few days and weeks.
Background: Assessing short-term growth in humans is still fraught with difficulties. Especially when looking for small variations and increments, such as mini growth spurts, high precision instruments or frequent measurements are necessary. Daily measurements however require a lot of effort, both for anthropologists and for the subjects. Therefore, new sophisticated approaches are needed that reduce fluctuations and reveal underlying patterns.
Objectives: Changepoints are abrupt variations in the properties of time series data. In the context of growth, such variations could be variation in mean height. By adjusting the variance and using different growth models, we assessed the ability of changepoint analysis to analyse short-term growth and detect mini growth spurts.
Sample and Methods: We performed Bayesian changepoint analysis on simulated growth data using the bcp package in R. Simulated growth patterns included stasis, linear growth, catch-up growth, and mini growth spurts. Specificity and a normalised variant of the Matthews correlation coefficient (MCC) were used to assess the algorithm’s performance. Welch’s t-test was used to compare differences of the mean.
Results: First results show that changepoint analysis can detect mini growth spurts. However, the ability to detect mini growth spurts is highly dependent on measurement error. Data preparation, such as ranking and rotating time series data, showed negligible improvements. Missing data was an issue and may affect the prediction quality of the classification metrics.
Conclusion: Changepoint analysis is a promising tool to analyse short-term growth. However, further optimisation and analysis of real growth data is needed to make broader generalisations.
Human growth data analysis and statistics – the 5th Gülpe International Student Summer School
(2023)
The Summer School in Gülpe (Ecological Station of the University of Potsdam) offers an exceptional learning opportunity for students to apply their knowledge and skills to real-world problems. With the guidance of experienced human biologists, statisticians, and programmers, students have the unique chance to analyze their own data and gain valuable insights. This interdisciplinary setting not only bridges different research areas but also leads to highly valuable outputs. The progress of students within just a few days is truly remarkable, especially when they are motivated and receive immediate feedback on their questions, problems, and results. The Summer School covers a wide range of topics, with this year’s focus mainly on two areas: understanding the impact of socioeconomic and physiological factors on human development and mastering statistical techniques for analyzing data such as changepoint analysis and the St. Nicolas House Analysis (SNHA) to visualize interacting variables. The latter technique, born out of the Summer School’s emphasis on gaining comprehensive data insights and understanding major relationships, has proven to be a valuable tool for researchers in the field. The articles in this special issue demonstrate that the Summer School in Gülpe stands as a testament to the power of practical learning and collaboration. Students who attend not only gain hands-on experience but also benefit from the expertise of professionals and the opportunity to engage with peers from diverse disciplines.
No evidence of growth impairment after forced migration in Polish school children after World War II
(2023)
Background: Migration is omnipresent. It can come hand in hand with emotional stress which is known to influence the growth of children.
Objective: The aim of this study was to analyse whether type of migration (forced or voluntary) and the geographic direction had influenced the growth of Polish children after World War II.
Sample and Methods: A sub dataset of 2,208 individuals between the ages of 2-20, created from data of the 2nd Polish Anthropological Survey carried out in 1966–1969, including anthropometrical data and social and demographic information based on questionnaire, was used to analyse migration effects.
Results: No association could be found between the direction of migration and the height of the children. The confidence intervals of the means of all classified migration categories overlap significantly and the effect size of the influence of migration category on height is ds=.140, which is too low to see any effects, even if there were one.
Conclusion: Neither forced nor voluntary migration in Poland after World War II led to a change in height in children of migrating families.
Nutrition, size, and tempo
(2023)
Nutrition is a prerequisite, but not a regulator of growth. Growth is defined as increase in size over time. The understanding of growth includes an understanding of the binary concept of physical time and individual tempo. Excess food causes tempo acceleration. Food restriction delays tempo. Tempo reflects the pace of life. It is a dynamic physical response to a broad spectrum of social, economic, political, and emotional (SEPE) factors and can affect life expectancy. Variations in tempo create distortions of the z-score patterns of height and weight. Illness or intermediate food shortage lead to intermediate halts in development and create short dips in the z-score patterns. Children who develop throughout life at delayed pace usually run at lower z-scores for height and weight, and show a characteristic adolescent trough; children who develop throughout life at faster than average pace usually run at higher z-scores and show a characteristic adolescent peak in their z-score patterns. During adolescence, almost half of the height variance is due to tempo variation. There is not one tempo for the whole body. Different organ systems grow and mature at different pace.
What does stunting tell us?
(2023)
Stunting is commonly linked with undernutrition. Yet, already after World War I, German pediatricians questioned this link and stated that no association exists between nutrition and height. Recent analyses within different populations of Low- and middle-income countries with high rates of stunted children failed to support the assumption that stunted children have a low BMI and skinfold sickness as signs of severe caloric deficiency. So, stunting is not a synonym of malnutrition. Parental education level has a positive influence on body height in stunted populations, e.g., in India and in Indonesia. Socially disadvantaged children tend to be shorter and lighter than children from affluent families.
Humans are social mammals; they regulate growth similar to other social mammals. Also in humans, body height is strongly associated with the position within the social hierarchy, reflecting the personal and group-specific social, economic, political, and emotional environment. These non-nutritional impact factors on growth are summarized by the concept of SEPE (Social-Economic-Political-Emotional) factors. SEPE reflects on prestige, dominance-subordination, social identity, and ego motivation of individuals and social groups.
The St. Nicolas House Algorithm (SNHA) finds association chains of direct dependent variables in a data set. The dependency is based on the correlation coefficient, which is visualized as an undirected graph. The network prediction is improved by a bootstrap routine. It enables the computation of the empirical p-value, which is used to evaluate the significance of the predicted edges. Synthetic data generated with the Monte Carlo method were used to firstly compare the Python package with the original R package, and secondly to evaluate the predicted network using the sensitivity, specificity, balanced classification rate and the Matthew's correlation coefficient (MCC). The Python implementation yields the same results as the R package. Hence, the algorithm was correctly ported into Python. The SNHA scores high specificity values for all tested graphs. For graphs with high edge densities, the other evaluation metrics decrease due to lower sensitivity, which could be partially improved by using bootstrap,while for graphs with low edge densities the algorithm achieves high evaluation scores. The empirical p-values indicated that the predicted edges indeed are significant.
The deficiency of a (bio)chemical reaction network can be conceptually interpreted as a measure of its ability to support exotic dynamical behavior and/or multistationarity. The classical definition of deficiency relates to the capacity of a network to permit variations of the complex formation rate vector at steady state, irrespective of the network kinetics. However, the deficiency is by definition completely insensitive to the fine details of the directionality of reactions as well as bounds on reaction fluxes. While the classical definition of deficiency can be readily applied in the analysis of unconstrained, weakly reversible networks, it only provides an upper bound in the cases where relevant constraints on reaction fluxes are imposed. Here we propose the concept of effective deficiency, which provides a more accurate assessment of the network’s capacity to permit steady state variations at the complex level for constrained networks of any reversibility patterns. The effective deficiency relies on the concept of nonstoichiometric balanced complexes, which we have already shown to be present in real-world biochemical networks operating under flux constraints. Our results demonstrate that the effective deficiency of real-world biochemical networks is smaller than the classical deficiency, indicating the effects of reaction directionality and flux bounds on the variation of the complex formation rate vector at steady state.
Introduction Flux phenotypes from different organisms and growth conditions allow better understanding of differential metabolic networks functions. Fluxes of metabolic reactions represent the integrated outcome of transcription, translation, and post-translational modifications, and directly affect growth and fitness. However, fluxes of intracellular metabolic reactions cannot be directly measured, but are estimated via metabolic flux analysis (MFA) that integrates data on isotope labeling patterns of metabolites with metabolic models. While the application of metabolomics technologies in photosynthetic organisms have resulted in unprecedented data from 13CO2-labeling experiments, the bottleneck in flux estimation remains the application of isotopically nonstationary MFA (INST-MFA). INST-MFA entails fitting a (large) system of coupled ordinary differential equations, with metabolite pools and reaction fluxes as parameters. Here, we focus on the Calvin-Benson cycle (CBC) as a key pathway for carbon fixation in photosynthesizing organisms and ask if approaches other than classical INST-MFA can provide reliable estimation of fluxes for reactions comprising this pathway.
Methods First, we show that flux estimation with the labeling patterns of all CBC intermediates can be formulated as a single constrained regression problem, avoiding the need for repeated simulation of time-resolved labeling patterns.
Results We then compare the flux estimates of the simulation-free constrained regression approach with those obtained from the classical INST-MFA based on labeling patterns of metabolites from the microalgae Chlamydomonas reinhardtii, Chlorella sorokiniana and Chlorella ohadii under different growth conditions.
Discussion Our findings indicate that, in data-rich scenarios, simulation-free regression-based approaches provide a suitable alternative for flux estimation from classical INST-MFA since we observe a high qualitative agreement (rs=0.89) to predictions obtained from INCA, a state-of-the-art tool for INST-MFA.
Protein-protein-interactions play an important role in many cellular functions. Quantitative non-invasive techniques are applied in living cells to evaluate such interactions, thereby providing a broader understanding of complex biological processes. Fluorescence fluctuation spectroscopy describes a group of quantitative microscopy approaches for the characterization of molecular interactions at single cell resolution. Through the obtained molecular brightness, it is possible to determine the oligomeric state of proteins. This is usually achieved by fusing fluorescent proteins (FPs) to the protein of interest. Recently, the number of novel green FPs has increased, with consequent improvements to the quality of fluctuation-based measurements. The photophysical behavior of FPs is influenced by multiple factors (including photobleaching, protonation-induced "blinking" and long-lived dark states). Assessing these factors is critical for selecting the appropriate fluorescent tag for live cell imaging applications. In this work, we focus on novel green FPs that are extensively used in live cell imaging. A systematic performance comparison of several green FPs in living cells under different pH conditions using Number & Brightness (N & B) analysis and scanning fluorescence correlation spectroscopy was performed. Our results show that the new FP Gamillus exhibits higher brightness at the cost of lower photostability and fluorescence probability (pf), especially at lower pH. mGreenLantern, on the other hand, thanks to a very high pf, is best suited for multimerization quantification at neutral pH. At lower pH, mEGFP remains apparently the best choice for multimerization investigation. These guidelines provide the information needed to plan quantitative fluorescence microscopy involving these FPs, both for general imaging or for protein-protein-interactions quantification via fluorescence fluctuation-based methods.
Genomic and epigenomic determinants of heat stress-induced transcriptional memory in Arabidopsis
(2023)
Background
Transcriptional regulation is a key aspect of environmental stress responses. Heat stress induces transcriptional memory, i.e., sustained induction or enhanced re-induction of transcription, that allows plants to respond more efficiently to a recurrent HS. In light of more frequent temperature extremes due to climate change, improving heat tolerance in crop plants is an important breeding goal. However, not all heat stress-inducible genes show transcriptional memory, and it is unclear what distinguishes memory from non-memory genes. To address this issue and understand the genome and epigenome architecture of transcriptional memory after heat stress, we identify the global target genes of two key memory heat shock transcription factors, HSFA2 and HSFA3, using time course ChIP-seq.
Results
HSFA2 and HSFA3 show near identical binding patterns. In vitro and in vivo binding strength is highly correlated, indicating the importance of DNA sequence elements. In particular, genes with transcriptional memory are strongly enriched for a tripartite heat shock element, and are hallmarked by several features: low expression levels in the absence of heat stress, accessible chromatin environment, and heat stress-induced enrichment of H3K4 trimethylation. These results are confirmed by an orthogonal transcriptomic data set using both de novo clustering and an established definition of memory genes.
Conclusions
Our findings provide an integrated view of HSF-dependent transcriptional memory and shed light on its sequence and chromatin determinants, enabling the prediction and engineering of genes with transcriptional memory behavior.
Spatial and temporal variation in perceived predation risk is an important determinant of movement and foraging activity of animals. Foraging in this landscape of fear, individuals need to decide where and when to move, and what resources to choose. Foraging theory predicts the outcome of these decisions based on energetic trade-offs, but complex interactions between perceived predation risk and preferences of foragers for certain functional traits of their resources are rarely considered. Here, we studied the interactive effects of perceived predation risk on food trait preferences and foraging behavior in bank voles (Myodes glareolus) in experimental landscapes. Individuals (n = 19) were subjected for periods of 24 h to two extreme, risk-uniform landscapes (either risky or safe), containing 25 discrete food patches, filled with seeds of four plant species in even amounts. Seeds varied in functional traits: size, nutrients, and shape. We evaluated whether and how risk modifies forager preference for functional traits. We also investigated whether perceived risk and distance from shelter affected giving-up density (GUD), time in patches, and number of patch visits. In safe landscapes, individuals increased time spent in patches, lowered GUD and visited distant patches more often compared to risky landscapes. Individuals preferred bigger seeds independent of risk, but in the safe treatment they preferred fat-rich over carb-rich seeds. Thus, higher densities of resource levels remained in risky landscapes, while in safe landscapes resource density was lower and less diverse due to selective foraging. Our results suggest that the interaction of perceived risk and dietary preference adds an additional layer to the cascading effects of a landscape of fear which affects biodiversity at resource level.
The oil palm (Elaeis guineensis Jacq.) produces a large amount of oil from the fruit. However, increasing the oil production in this fruit is still challenging. A recent study has shown that starch metabolism is essential for oil synthesis in fruit-producing species. Therefore, the transcriptomic analysis by RNA-seq was performed to observe gene expression alteration related to starch metabolism genes throughout the maturity stages of oil palm fruit with different oil yields. Gene expression profiles were examined with three different oil yields group (low, medium, and high) at six fruit development phases (4, 8, 12, 16, 20, and 22 weeks after pollination). We successfully identified and analyzed differentially expressed genes in oil palm mesocarps during development. The results showed that the transcriptome profile for each developmental phase was unique. Sucrose flux to the mesocarp tissue, rapid starch turnover, and high glycolytic activity have been identified as critical factors for oil production in oil palms. For starch metabolism and the glycolytic pathway, we identified specific gene expressions of enzyme isoforms (isozymes) that correlated with oil production, which may determine the oil content. This study provides valuable information for creating new high-oil-yielding palm varieties via breeding programs or genome editing approaches.
Starch has been a convenient, economically important polymer with substantial applications in the food and processing industry. However, native starches present restricted applications, which hinder their industrial usage. Therefore, modification of starch is carried out to augment the positive characteristics and eliminate the limitations of the native starches. Modifications of starch can result in generating novel polymers with numerous functional and value-added properties that suit the needs of the industry. Here, we summarize the possible starch modifications in planta and outside the plant system (physical, chemical, and enzymatic) and their corresponding applications. In addition, this review will highlight the implications of each starch property adjustment.
Keeping cool on hot days
(2023)
Long-lived organisms are likely to respond to a rapidly changing climate with behavioral flexibility. Animals inhabiting the arid parts of southern Africa face a particularly rapid rise in temperature which in combination with food and water scarcity places substantial constraints on the ability of animals to tolerate heat. We investigated how three species of African antelope-springbok Antidorcas marsupialis, kudu Tragelaphus strepsiceros and eland T. oryx-differing in body size, habitat preference and movement ecology, change their activity in response to extreme heat in an arid savanna. Serving as a proxy for activity, dynamic body acceleration data recorded every five minutes were analyzed for seven to eight individuals per species for the three hottest months of the year. Activity responses to heat during the hottest time of day (the afternoons) were investigated and diel activity patterns were compared between hot and cool days. Springbok, which prefer open habitat, are highly mobile and the smallest of the species studied, showed the greatest decrease in activity with rising temperature. Furthermore, springbok showed reduced mean activity over the 24 h cycle on hot days compared to cool days. Large-bodied eland seemed less affected by afternoon heat than springbok. While eland also reduced diurnal activity on hot days compared to cool days, they compensated for this by increasing nocturnal activity, possibly because their predation risk is lower. Kudu, which are comparatively sedentary and typically occupy shady habitat, seemed least affected during the hottest time of day and showed no appreciable difference in diel activity patterns between hot and cool days. The interplay between habitat preference, body size, movement patterns, and other factors seems complex and even sub-lethal levels of heat stress have been shown to impact an animal's long-term survival and reproduction. Thus, differing heat tolerances among species could result in a shift in the composition of African herbivore communities as temperatures continue to rise, with significant implications for economically important wildlife-based land use and conservation.
The heat is on
(2023)
Climate conditions severely impact the activity and, consequently, the fitness of wildlife species across the globe. Wildlife can respond to new climatic conditions, but the pace of human-induced change limits opportunities for adaptation or migration. Thus, how these changes affect behavior, movement patterns, and activity levels remains unclear. In this study, we investigate how extreme weather conditions affect the activity of European hares (Lepus europaeus) during their peak reproduction period. When hares must additionally invest energy in mating, prevailing against competitors, or lactating, we investigated their sensitivities to rising temperatures, wind speed, and humidity. To quantify their activity, we used the overall dynamic body acceleration (ODBA) calculated from tri-axial acceleration measurements of 33 GPS-collared hares. Our analysis revealed that temperature, humidity, and wind speed are important in explaining changes in activity, with a strong response for high temperatures above 25 & DEG;C and the highest change in activity during temperature extremes of over 35 & DEG;C during their inactive period. Further, we found a non-linear relationship between temperature and activity and an interaction of activity changes between day and night. Activity increased at higher temperatures during the inactive period (day) and decreased during the active period (night). This decrease was strongest during hot tropical nights. At a stage of life when mammals such as hares must substantially invest in reproduction, the sensitivity of females to extreme temperatures was particularly pronounced. Similarly, both sexes increased their activity at high humidity levels during the day and low wind speeds, irrespective of the time of day, while the effect of humidity was stronger for males. Our findings highlight the importance of understanding the complex relationships between extreme weather conditions and mammal behavior, critical for conservation and management. With ongoing climate change, extreme weather events such as heat waves and heavy rainfall are predicted to occur more often and last longer. These events will directly impact the fitness of hares and other wildlife species and hence the population dynamics of already declining populations across Europe.
The capillary-venous pathology cerebral cavernous malformation (CCM) is caused by loss of CCM1/Krev interaction trapped protein 1 (KRIT1), CCM2/MGC4607, or CCM3/PDCD10 in some endothelial cells. Mutations of CCM genes within the brain vasculature can lead to recurrent cerebral hemorrhages. Pharmacological treatment options are urgently needed when lesions are located in deeply-seated and in-operable regions of the central nervous system. Previous pharmacological suppression screens in disease models of CCM led to the discovery that treatment with retinoic acid improved CCM phenotypes. This finding raised a need to investigate the involvement of retinoic acid in CCM and test whether it has a curative effect in preclinical mouse models. Here, we show that components of the retinoic acid synthesis and degradation pathway are transcriptionally misregulated across disease models of CCM. We complemented this analysis by pharmacologically modifying retinoic acid levels in zebrafish and human endothelial cell models of CCM, and in acute and chronic mouse models of CCM. Our pharmacological intervention studies in CCM2-depleted human umbilical vein endothelial cells (HUVECs) and krit1 mutant zebrafish showed positive effects when retinoic acid levels were increased. However, therapeutic approaches to prevent the development of vascular lesions in adult chronic murine models of CCM were drug regiment-sensitive, possibly due to adverse developmental effects of this hormone. A treatment with high doses of retinoic acid even worsened CCM lesions in an adult chronic murine model of CCM. This study provides evidence that retinoic acid signaling is impaired in the CCM pathophysiology and suggests that modification of retinoic acid levels can alleviate CCM phenotypes.
Cell-level systems biology model to study inflammatory bowel diseases and their treatment options
(2023)
To help understand the complex and therapeutically challenging inflammatory bowel diseases (IBDs), we developed a systems biology model of the intestinal immune system that is able to describe main aspects of IBD and different treatment modalities thereof. The model, including key cell types and processes of the mucosal immune response, compiles a large amount of isolated experimental findings from literature into a larger context and allows for simulations of different inflammation scenarios based on the underlying data and assumptions. In the context of a large and diverse virtual IBD population, we characterized the patients based on their phenotype (in contrast to healthy individuals, they developed persistent inflammation after a trigger event) rather than on a priori assumptions on parameter differences to a healthy individual. This allowed to reproduce the enormous diversity of predispositions known to lead to IBD. Analyzing different treatment effects, the model provides insight into characteristics of individual drug therapy. We illustrate for anti-TNF-alpha therapy, how the model can be used (i) to decide for alternative treatments with best prospects in the case of nonresponse, and (ii) to identify promising combination therapies with other available treatment options.
Progressive habitat fragmentation threatens plant species with narrow habitat requirements. While local environmental conditions define population growth rates and recruitment success at the patch level, dispersal is critical for population viability at the landscape scale. Identifying the dynamics of plant meta-populations is often confounded by the uncertainty about soil-stored population compartments. We combined a landscape-scale assessment of an amphibious plant's population structure with measurements of dispersal complexity in time to track dispersal and putative shifts in functional connectivity. Using 13 microsatellite markers, we analyzed the genetic structure of extant Oenanthe aquatica populations and their soil seed banks in a kettle hole system to uncover hidden connectivity among populations in time and space. Considerable spatial genetic structure and isolation-by-distance suggest limited gene flow between sites. Spatial isolation and patch size showed minor effects on genetic diversity. Genetic similarity found among extant populations and their seed banks suggests increased local recruitment, despite some evidence of migration and recent colonization. Results indicate stepping-stone dispersal across adjacent populations. Among permanent and ephemeral demes the resulting meta-population demography could be determined by source-sink dynamics. Overall, these spatiotemporal connectivity patterns support mainland-island dynamics in our system, highlighting the importance of persistent seed banks as enduring sources of genetic diversity.
Metabolic engineering of microalgae offers a promising solution for sustainable biofuel production, and rational design of engineering strategies can be improved by employing metabolic models that integrate enzyme turnover numbers. However, the coverage of turnover numbers for Chlamydomonas reinhardtii, a model eukaryotic microalga accessible to metabolic engineering, is 17-fold smaller compared to the heterotrophic cell factory Saccharomyces cerevisiae. Here we generate quantitative protein abundance data of Chlamydomonas covering 2337 to 3708 proteins in various growth conditions to estimate in vivo maximum apparent turnover numbers. Using constrained-based modeling we provide proxies for in vivo turnover numbers of 568 reactions, representing a 10-fold increase over the in vitro data for Chlamydomonas. Integration of the in vivo estimates instead of in vitro values in a metabolic model of Chlamydomonas improved the accuracy of enzyme usage predictions. Our results help in extending the knowledge on uncharacterized enzymes and improve biotechnological applications of Chlamydomonas.
The physiological dependence of animals on dietary intake of vitamins, amino acids, and fatty acids is ubiquitous. Sharp differences in the availability of these vital dietary biomolecules among different resources mean that consumers must adopt a range of strategies to meet their physiological needs. We review the emerging work on omega-3 long-chain polyunsaturated fatty acids, focusing predominantly on predator-prey interactions, to illustrate that trade-off between capacities to consume resources rich in vital biomolecules and internal synthesis capacity drives differences in phenotype and fitness of consumers. This can then feedback to impact ecosystem functioning. We outline how focus on vital dietary biomolecules in eco-eco-devo dynamics can improve our understanding of anthropogenic changes across multiple levels of biological organization.
The European Union is highly dependent on soybean imports from overseas to meet its protein demands. Individual Member States have been quick to declare self-sufficiency targets for plant-based proteins, but detailed strategies are still lacking. Rising global temperatures have painted an image of a bright future for soybean production in Europe, but emerging climatic risks such as drought have so far not been included in any of those outlooks.
Here, we present simulations of future soybean production and the most prominent risk factors across Europe using an ensemble of climate and soybean growth models. Projections suggest a substantial increase in potential soybean production area and productivity in Central Europe, while southern European production would become increasingly dependent on supplementary irrigation. Average productivity would rise by 8.3% (RCP 4.5) to 8.7% (RCP 8.5) as a result of improved growing conditions (plant physiology benefiting from rising temperature and CO2 levels) and farmers adapting to them by using cultivars with longer phenological cycles. Suitable production area would rise by 31.4% (RCP 4.5) to 37.7% (RCP 8.5) by the mid-century, contributing considerably more than productivity increase to the production potential for closing the protein gap in Europe.
While wet conditions at harvest and incidental cold spells are the current key challenges for extending soybean production, the models and climate data analysis anticipate that drought and heat will become the dominant limitations in the future. Breeding for heat-tolerant and water-efficient genotypes is needed to further improve soybean adaptation to changing climatic conditions.
This study focuses on three key aspects: (a) crude throat swab samples in a viral transport medium (VTM) as templates for RT-LAMP reactions; (b) a biotinylated DNA probe with enhanced specificity for LFA readouts; and (c) a digital semi-quantification of LFA readouts. Throat swab samples from SARS-CoV-2 positive and negative patients were used in their crude (no cleaning or pre-treatment) forms for the RT-LAMP reaction. The samples were heat-inactivated but not treated for any kind of nucleic acid extraction or purification. The RT-LAMP (20 min processing time) product was read out by an LFA approach using two labels: FITC and biotin. FITC was enzymatically incorporated into the RT-LAMP amplicon with the LF-LAMP primer, and biotin was introduced using biotinylated DNA probes, specifically for the amplicon region after RT-LAMP amplification. This assay setup with biotinylated DNA probe-based LFA readouts of the RT-LAMP amplicon was 98.11% sensitive and 96.15% specific. The LFA result was further analysed by a smartphone-based IVD device, wherein the T-line intensity was recorded. The LFA T-line intensity was then correlated with the qRT-PCR Ct value of the positive swab samples. A digital semi-quantification of RT-LAMP-LFA was reported with a correlation coefficient of R2 = 0.702. The overall RT-LAMP-LFA assay time was recorded to be 35 min with a LoD of three RNA copies/µL (Ct-33). With these three advancements, the nucleic acid testing-point of care technique (NAT-POCT) is exemplified as a versatile biosensor platform with great potential and applicability for the detection of pathogens without the need for sample storage, transportation, or pre-processing.
Background
Teleost fishes comprise more than half of the vertebrate species. Within teleosts, most phylogenies consider the split between Osteoglossomorpha and Euteleosteomorpha/Otomorpha as basal, preceded only by the derivation of the most primitive group of teleosts, the Elopomorpha. While Osteoglossomorpha are generally species poor, the taxon contains the African weakly electric fish (Mormyroidei), which have radiated into numerous species. Within the mormyrids, the genus Campylomormyrus is mostly endemic to the Congo Basin. Campylomormyrus serves as a model to understand mechanisms of adaptive radiation and ecological speciation, especially with regard to its highly diverse species-specific electric organ discharges (EOD). Currently, there are few well-annotated genomes available for electric fish in general and mormyrids in particular. Our study aims at producing a high-quality genome assembly and to use this to examine genome evolution in relation to other teleosts. This will facilitate further understanding of the evolution of the osteoglossomorpha fish in general and of electric fish in particular.
Results
A high-quality weakly electric fish (C. compressirostris) genome was produced from a single individual with a genome size of 862 Mb, consisting of 1,497 contigs with an N50 of 1,399 kb and a GC-content of 43.69%. Gene predictions identified 34,492 protein-coding genes, which is a higher number than in the two other available Osteoglossomorpha genomes of Paramormyrops kingsleyae and Scleropages formosus. A Computational Analysis of gene Family Evolution (CAFE5) comparing 33 teleost fish genomes suggests an overall faster gene family turnover rate in Osteoglossomorpha than in Otomorpha and Euteleosteomorpha. Moreover, the ratios of expanded/contracted gene family numbers in Osteoglossomorpha are significantly higher than in the other two taxa, except for species that had undergone an additional genome duplication (Cyprinus carpio and Oncorhynchus mykiss). As potassium channel proteins are hypothesized to play a key role in EOD diversity among species, we put a special focus on them, and manually curated 16 Kv1 genes. We identified a tandem duplication in the KCNA7a gene in the genome of C. compressirostris.
Conclusions
We present the fourth genome of an electric fish and the third well-annotated genome for Osteoglossomorpha, enabling us to compare gene family evolution among major teleost lineages. Osteoglossomorpha appear to exhibit rapid gene family evolution, with more gene family expansions than contractions. The curated Kv1 gene family showed seven gene clusters, which is more than in other analyzed fish genomes outside Osteoglossomorpha. The KCNA7a, encoding for a potassium channel central for EOD production and modulation, is tandemly duplicated which may related to the diverse EOD observed among Campylomormyrus species.
The use of automated tools to reconstruct lipid metabolic pathways is not warranted in plants. Here, the authors construct Plant Lipid Module for Arabidopsis rosette using constraint-based modeling, demonstrate its integration in other plant metabolic models, and use it to dissect the genetic architecture of lipid metabolism.
Lipids play fundamental roles in regulating agronomically important traits. Advances in plant lipid metabolism have until recently largely been based on reductionist approaches, although modulation of its components can have system-wide effects. However, existing models of plant lipid metabolism provide lumped representations, hindering detailed study of component modulation. Here, we present the Plant Lipid Module (PLM) which provides a mechanistic description of lipid metabolism in the Arabidopsis thaliana rosette. We demonstrate that the PLM can be readily integrated in models of A. thaliana Col-0 metabolism, yielding accurate predictions (83%) of single lethal knock-outs and 75% concordance between measured transcript and predicted flux changes under extended darkness. Genome-wide associations with fluxes obtained by integrating the PLM in diel condition- and accession-specific models identify up to 65 candidate genes modulating A. thaliana lipid metabolism. Using mutant lines, we validate up to 40% of the candidates, paving the way for identification of metabolic gene function based on models capturing natural variability in metabolism.