Hymenopteran-specific TRPA channel from the Texas leaf cutter ant (Atta texana) is heat and cold activated and expression correlates with environmental temperature.

Leaf cutting ants of the genus Atta cultivate fungal gardens, carefully modifying environmental conditions to maintain optimal temperature for fungal growth. Antennal nerves from Atta are highly temperature sensitive, but the underlying molecular sensor is unknown. Here, we utilize Atta texana (Texas leaf cutter ant) to investigate the molecular basis of ant temperature sensation and how it might have evolved as the range expanded northeast across Texas from ancestral populations in Mexico. We focus on transient receptor potential (TRP) channel genes, the best characterized temperature sensor proteins in animals. Atta texana antennae express 6 of 13 Hymenopteran TRP channel genes and sequences are under a mix of relaxed and intensified selection. In a behavioral assay, we find A. texana workers prefer 24 °C (range 21-26 °C) for fungal growth. There was no evidence of regulatory evolution across a temperature transect in Texas, but instead Hymenoptera-specific TRPA (HsTRPA) expression highly correlated with ambient temperature. When expressed in vitro, HsTRPA from A. texana is temperature activated with Q10 values exceeding 100 on initial exposure to temperatures above 33 °C. Surprisingly, HsTRPA also appears to be activated by cooling, and therefore to our knowledge, the first non-TRPA1 ortholog to be described with dual heat/cold activation and the first in any invertebrate.

Preserving Derivative Information while Transforming Neuronal Curves.

The international neuroscience community is building the first comprehensive atlases of brain cell types to understand how the brain functions from a higher resolution, and more integrated perspective than ever before. In order to build these atlases, subsets of neurons (e.g. serotonergic neurons, prefrontal cortical neurons etc.) are traced in individual brain samples by placing points along dendrites and axons. Then, the traces are mapped to common coordinate systems by transforming the positions of their points, which neglects how the transformation bends the line segments in between. In this work, we apply the theory of jets to describe how to preserve derivatives of neuron traces up to any order. We provide a framework to compute possible error introduced by standard mapping methods, which involves the Jacobian of the mapping transformation. We show how our first order method improves mapping accuracy in both simulated and real neuron traces under random diffeomorphisms. Our method is freely available in our open-source Python package brainlit.

Life history, nest longevity, sex ratio, and nest architecture of the fungus-growing ant Mycetosoritis hartmanni (Formicidae: Attina).

Mycetosoritis hartmanni is a rarely collected fungus-farming ant of North America. We describe life history and nest architecture for a M. hartmanni population in central Texas, USA. Colonies are monogynous with typically less than 100 workers (average 47.6 workers, maximum 148 workers). Nests occur always in sand and have a uniform architecture with 1-3 underground garden chambers arranged along a vertical tunnel, with the deepest gardens 50-70 cm deep. Foragers are active primarily between April and October. After reduced activity between November and February, egg laying by queens resumes in April, and the first worker pupae develop in early June. Reproductive females and males are reared primarily in July and August, with proportionally more females produced early in summer (protogyny). Mating flights and founding of new nests by mated females occur in late June to August, but may extend through September. For a cohort of 150 established nests (nests that had survived at least one year after nest founding), the estimated mortality rate was 0.41-0.53, the estimated average lifespan for these nests was 1.9-2.5 years, and the longest-living nests were observed to live for 6 years. These life-history parameters for M. hartmanni in central Texas are consistent with information from additional M. hartmanni nests observed throughout the range of this species from eastern Louisiana to southern Texas. Throughout its range in the USA, M. hartmanni can be locally very abundant in sun-exposed, sandy soil. Abundance of M. hartmanni seems so far relatively unaffected by invasive fire ants, and at present M. hartmanni does not appear to be an endangered species.

Preserving Derivative Information while Transforming Neuronal Curves.

The international neuroscience community is building the first comprehensive atlases of brain cell types to understand how the brain functions from a higher resolution, and more integrated perspective than ever before. In order to build these atlases, subsets of neurons (e.g. serotonergic neurons, prefrontal cortical neurons etc.) are traced in individual brain samples by placing points along dendrites and axons. Then, the traces are mapped to common coordinate systems by transforming the positions of their points, which neglects how the transformation bends the line segments in between. In this work, we apply the theory of jets to describe how to preserve derivatives of neuron traces up to any order. We provide a framework to compute possible error introduced by standard mapping methods, which involves the Jacobian of the mapping transformation. We show how our first order method improves mapping accuracy in both simulated and real neuron traces, though zeroth order mapping is generally adequate in our real data setting. Our method is freely available in our open-source Python package brainlit.

Preserving Derivative Information while Transforming Neuronal Curves.

The international neuroscience community is building the first comprehensive atlases of brain cell types to understand how the brain functions from a higher resolution, and more integrated perspective than ever before. In order to build these atlases, subsets of neurons (e.g. serotonergic neurons, prefrontal cortical neurons etc.) are traced in individual brain samples by placing points along dendrites and axons. Then, the traces are mapped to common coordinate systems by transforming the positions of their points, which neglects how the transformation bends the line segments in between. In this work, we apply the theory of jets to describe how to preserve derivatives of neuron traces up to any order. We provide a framework to compute possible error introduced by standard mapping methods, which involves the Jacobian of the mapping transformation. We show how our first order method improves mapping accuracy in both simulated and real neuron traces under random diffeomorphisms. Our method is freely available in our open-source Python package brainlit.

Statistical Analysis in the German National Cohort (NAKO) - Specific Aspects and General Recommendations.

The German National Cohort (NAKO) is an ongoing, prospective multicenter cohort study, which started recruitment in 2014 and includes more than 205,000 women and men aged 19-74 years. The study data will be available to the global research community for analyses. Although the ultimate decision about the analytic methods will be made by the respective investigator, in this paper we provide the basis for a harmonized approach to the statistical analyses in the NAKO. We discuss specific aspects of the study (e.g., data collection, weighting to account for the sampling design), but also give general recommendations which may apply to other large cohort studies as well.

Microbiome breeding: conceptual and practical issues.

Microbiome breeding is a new artificial selection technique that seeks to change the genetic composition of microbiomes in order to benefit plant or animal hosts. Recent experimental and theoretical analyses have shown that microbiome breeding is possible whenever microbiome-encoded genetic factors affect host traits (e.g., health) and microbiomes are transmissible between hosts with sufficient fidelity, such as during natural microbiome transmission between individuals of social animals, or during experimental microbiome transplanting between plants. To address misunderstandings that stymie microbiome-breeding programs, we (i) clarify and visualize the corresponding elements of microbiome selection and standard selection; (ii) elucidate the eco-evolutionary processes underlying microbiome selection within a quantitative genetic framework to summarize practical guidelines that optimize microbiome breeding; and (iii) characterize the kinds of host species most amenable to microbiome breeding.

Hidden Markov modeling for maximum probability neuron reconstruction.

Recent advances in brain clearing and imaging have made it possible to image entire mammalian brains at sub-micron resolution. These images offer the potential to assemble brain-wide atlases of neuron morphology, but manual neuron reconstruction remains a bottleneck. Several automatic reconstruction algorithms exist, but most focus on single neuron images. In this paper, we present a probabilistic reconstruction method, ViterBrain, which combines a hidden Markov state process that encodes neuron geometry with a random field appearance model of neuron fluorescence. ViterBrain utilizes dynamic programming to compute the global maximizer of what we call the most probable neuron path. We applied our algorithm to imperfect image segmentations, and showed that it can follow axons in the presence of noise or nearby neurons. We also provide an interactive framework where users can trace neurons by fixing start and endpoints. ViterBrain is available in our open-source Python package brainlit.

Artificial Selection on Microbiomes To Breed Microbiomes That Confer Salt Tolerance to Plants.

We develop a method to artificially select for rhizosphere microbiomes that confer salt tolerance to the model grass Brachypodium distachyon grown under sodium salt stress or aluminum salt stress. In a controlled greenhouse environment, we differentially propagated rhizosphere microbiomes between plants of a nonevolving, highly inbred plant population; therefore, only microbiomes evolved in our experiment, but the plants did not evolve in parallel. To maximize microbiome perpetuation when transplanting microbiomes between plants and, thus, maximize response to microbiome selection, we improved earlier methods by (i) controlling microbiome assembly when inoculating seeds at the beginning of each selection cycle; (ii) fractionating microbiomes before transfer between plants to harvest, perpetuate, and select on only bacterial and viral microbiome components; (iii) ramping of salt stress gradually from minor to extreme salt stress with each selection cycle to minimize the chance of overstressing plants; (iv) using two nonselection control treatments (e.g., nonselection microbial enrichment and null inoculation) that permit comparison to the improving fitness benefits that selected microbiomes impart on plants. Unlike previous methods, our selection protocol generated microbiomes that enhance plant fitness after only 1 to 3 rounds of microbiome selection. After nine rounds of microbiome selection, the effect of microbiomes selected to confer tolerance to aluminum salt stress was nonspecific (these artificially selected microbiomes equally ameliorate sodium and aluminum salt stresses), but the effect of microbiomes selected to confer tolerance to sodium salt stress was specific (these artificially selected microbiomes do not confer tolerance to aluminum salt stress). Plants with artificially selected microbiomes had 55 to 205% greater seed production than plants with unselected control microbiomes. IMPORTANCE We developed an experimental protocol that improves earlier methods of artificial selection on microbiomes and then tested the efficacy of our protocol to breed root-associated bacterial microbiomes that confer salt tolerance to a plant. Salt stress limits growth and seed production of crop plants, and artificially selected microbiomes conferring salt tolerance may ultimately help improve agricultural productivity. Unlike previous experiments of microbiome selection, our selection protocol generated microbiomes that enhance plant productivity after only 1 to 3 rounds of artificial selection on root-associated microbiomes, increasing seed production under extreme salt stress by 55 to 205% after nine rounds of microbiome selection. Although we artificially selected microbiomes under controlled greenhouse conditions that differ from outdoor conditions, increasing seed production by 55 to 205% under extreme salt stress is a remarkable enhancement of plant productivity compared to traditional plant breeding. We describe a series of additional experimental protocols that will advance insights into key parameters that determine efficacy and response to microbiome selection.

Fitting Splines to Axonal Arbors Quantifies Relationship Between Branch Order and Geometry.

Neuromorphology is crucial to identifying neuronal subtypes and understanding learning. It is also implicated in neurological disease. However, standard morphological analysis focuses on macroscopic features such as branching frequency and connectivity between regions, and often neglects the internal geometry of neurons. In this work, we treat neuron trace points as a sampling of differentiable curves and fit them with a set of branching B-splines. We designed our representation with the Frenet-Serret formulas from differential geometry in mind. The Frenet-Serret formulas completely characterize smooth curves, and involve two parameters, curvature and torsion. Our representation makes it possible to compute these parameters from neuron traces in closed form. These parameters are defined continuously along the curve, in contrast to other parameters like tortuosity which depend on start and end points. We applied our method to a dataset of cortical projection neurons traced in two mouse brains, and found that the parameters are distributed differently between primary, collateral, and terminal axon branches, thus quantifying geometric differences between different components of an axonal arbor. The results agreed in both brains, further validating our representation. The code used in this work can be readily applied to neuron traces in SWC format and is available in our open-source Python package brainlit: http://brainlit.neurodata.io/.

Complementary and alternative medicine is positively associated with religiousness/spirituality.

BACKGROUND: Complementary and alternative medicine (CAM) is used often by patients with different diseases. While some authors subsume religiousness and spirituality to CAM, others do not. The objective of the present study was to assess the prevalence and types of CAM usage as well as the participants' spirituality/religiousness in an outpatient department for endocrinology and metabolic diseases. METHODS: All individuals visiting the outpatient department at a German university hospital from April to June 2009 were offered a standardized questionnaire on the use of dietary supplements and alternative therapies as well as their religiousness/spirituality. Demographic and clinical data of 428 respondents were taken from the electronic health record. RESULTS: Of the respondents, 16.4% (n = 66) classified themselves to be religious/spiritual and 67.9% (n = 273) as not religious/spiritual. Women were more religious/spiritual than men (p = 0.02). 41.4% of the respondents used supplements and 27.4% additional therapies. The use of supplements and additional therapies was more frequent in people with higher religiousness/spirituality (p = 0.005 and p = 0.01,resp.) but there were no associations between religiousness/spirituality and the number of consultations, costs for drugs, appraisal of the physicians treatment methods, the perceived effectiveness of prescribed drugs, fear of late complications or of side effects. CONCLUSIONS: A higher religiousness/spirituality is associated with a more frequent use of supplements or additional therapies in individuals with endocrinopathies or metabolic diseases. As CAM has been shown to be associated with worse outcome, addressing religiousness/spirituality which stresses the responsibility of the person for his life might offer an additional resource and should be further studied.

[Nighttime transportation noise annoyance in Germany: personal and regional differences in the German National Cohort Study]. / Nächtliche Verkehrslärmbelästigung in Deutschland: individuelle und regionale Unterschiede in der NAKO Gesundheitsstudie.

BACKGROUND: Noise annoyance is associated with adverse health-related conditions and reduced wellbeing. Thereby, subjective noise annoyance depends on the objective noise exposure and is modified by personal and regional factors. OBJECTIVE: How many participants of the German National Cohort Study (GNC; NAKO Gesundheitsstudie) were annoyed by transportation noise during nighttime and what factors were associated with noise annoyance? MATERIALS AND METHODS: This cross-sectional analysis included 86,080 participants from 18 study centers, examined from 2014 to 2017. We used multinomial logistic regression to investigate associations of personal and regional factors to noise annoyance (slightly/moderately or strongly/extremely annoyed vs. not annoyed) mutually adjusting for all factors in the model. RESULTS: Two thirds of participants were not annoyed by transportation noise during nighttime and one in ten reported strong/extreme annoyance with highest percentages for the study centers Berlin-Mitte and Leipzig. The strongest associations were seen for factors related to the individual housing situation like the bedroom being positioned towards a major road (OR of being slightly/moderately annoyed: 4.26 [95% CI: 4.01;4.52]; OR of being strongly/extremely annoyed: 13.36 [95% CI: 12.47;14.32]) compared to a garden/inner courtyard. Participants aged 40-60 years and those in low- and medium-income groups reported greater noise annoyance compared to younger or older ones and those in the high-income group. CONCLUSION: In this study from Germany, transportation noise annoyance during nighttime varied by personal and regional factors.

[The baseline assessment of the German National Cohort (NAKO Gesundheitsstudie): participation in the examination modules, quality assurance, and the use of secondary data]. / Die Basiserhebung der NAKO Gesundheitsstudie: Teilnahme an den Untersuchungsmodulen, Qualitätssicherung und Nutzung von Sekundärdaten.

BACKGROUND: The German National Cohort (NAKO) is an interdisciplinary health study aimed at elucidating causes for common chronic diseases and detecting their preclinical stages. This article provides an overview of design, methods, participation in the examinations, and their quality assurance based on the midterm baseline dataset (MBD) of the recruitment. METHODS: More than 200,000 women and men aged 20-69 years derived from random samples of the German general population were recruited in 18 study centers (2014-2019). The data collection comprised physical examinations, standardized interviews and questionnaires, and the collection of biomedical samples for all participants (level 1). At least 20% of all participants received additional in-depth examinations (level 2), and 30,000 received whole-body magnet resonance imaging (MRI). Additional information will be collected through secondary data sources such as medical registries, health insurances, and pension funds. This overview is based on the MBD, which included 101,839 participants, of whom 11,371 received an MRI. RESULTS: The mean response proportion was 18%. The participation in the examinations was high with most of the modules performed by over 95%. Among MRI participants, 96% completed all 12 MRI sequences. More than 90% of the participants agreed to the use of complementary secondary and registry data. DISCUSSION: Individuals selected for the NAKO were willing to participate in all examinations despite the time-consuming program. The NAKO provides a central resource for population-based epidemiologic research and will contribute to developing innovative strategies for prevention, screening and prediction of chronic diseases.

Prospective relations between kindergarteners' executive function skills and their externalizing and internalizing behaviors.

Objective: Executive function difficulties have been identified as a transdiagnostic mechanism for the development of psychological disorders; however little is known about the relations between executive function and internalizing and externalizing behavior patterns, especially in young children. To address this gap in the literature, the current study examined the reciprocal relations between internalizing and externalizing behaviors and two component processes of executive function, inhibition, and working memory.Method: Sixty-nine five- and six-year old children were included in the current study. Maladaptive behaviors were measured using the Social Skills Rating Scale (SSRS). Inhibition was assessed using commission errors in the Preschool Continuous Performance Task (P-CPT), and working memory was measured using the Boxes task.Results: Results demonstrated a significant reciprocal relationship between externalizing behavior and inhibitory control (commission errors on the P-CPT), as well as between working memory and internalizing behaviors.Conclusion: The results have important implications for the development of early intervention programs. Suggestions for future research and limitations of the current work are discussed.

Potential Distribution of Six North American Higher-Attine Fungus-Farming Ant (Hymenoptera: Formicidae) Species.

Ants are among the most successful insects in Earth's evolutionary history. However, there is a lack of knowledge regarding range-limiting factors that may influence their distribution. The goal of this study was to describe the environmental factors (climate and soil types) that likely impact the ranges of five out of the eight most abundant Trachymyrmex species and the most abundant Mycetomoellerius species in the United States. Important environmental factors may allow us to better understand each species' evolutionary history. We generated habitat suitability maps using MaxEnt for each species and identified associated most important environmental variables. We quantified niche overlap between species and evaluated possible congruence in species distribution. In all but one model, climate variables were more important than soil variables. The distribution of M. turrifex (Wheeler, W.M., 1903) was predicted by temperature, specifically annual mean temperature (BIO1), T. arizonensis (Wheeler, W.M., 1907), T. carinatus, and T. smithi Buren, 1944 were predicted by precipitation seasonality (BIO15), T. septentrionalis (McCook, 1881) were predicted by precipitation of coldest quarter (BIO19), and T. desertorum (Wheeler, W.M., 1911) was predicted by annual flood frequency. Out of 15 possible pair-wise comparisons between each species' distributions, only one was statistically indistinguishable (T. desertorum vs T. septentrionalis). All other species distribution comparisons show significant differences between species. These models support the hypothesis that climate is a limiting factor in each species distribution and that these species have adapted to temperatures and water availability differently.

Far-Transfer Effects of Strategy-Based Working Memory Training.

We assessed the transfer effects of training working memory strategies to a novel problem-solving task. Previous WM training studies have produced little evidence for transfer across contexts. In the current study, 64 6- to 9-year-olds were randomly assigned to one of four training conditions: semantic and rehearsal training, semantic training only, rehearsal training only, and treated control group. All training groups performed significantly better on the transfer task than the control group, but training groups did not differ significantly from each other. Implications of the findings for cognitive interventions and future WM training studies are discussed.

Landscape genomics of an obligate mutualism: Concordant and discordant population structures between the leafcutter ant Atta texana and its two main fungal symbiont types.

To explore landscape genomics at the range limit of an obligate mutualism, we use genotyping-by-sequencing (ddRADseq) to quantify population structure and the effect of host-symbiont interactions between the northernmost fungus-farming leafcutter ant Atta texana and its two main types of cultivated fungus. Genome-wide differentiation between ants associated with either of the two fungal types is of the same order of magnitude as differentiation associated with temperature and precipitation across the ant's entire range, suggesting that specific ant-fungus genome-genome combinations may have been favoured by selection. For the ant hosts, we found a broad cline of genetic structure across the range, and a reduction of genetic diversity along the axis of range expansion towards the range margin. This population-genetic structure was concordant between the ants and one cultivar type (M-fungi, concordant clines) but discordant for the other cultivar type (T-fungi). Discordance in population-genetic structures between ant hosts and a fungal symbiont is surprising because the ant farmers codisperse with their vertically transmitted fungal symbionts. Discordance implies that (a) the fungi disperse also through between-nest horizontal transfer or other unknown mechanisms, and (b) genetic drift and gene flow can differ in magnitude between each partner and between different ant-fungus combinations. Together, these findings imply that variation in the strength of drift and gene flow experienced by each mutualistic partner affects adaptation to environmental stress at the range margin, and genome-genome interactions between host and symbiont influence adaptive genetic differentiation of the host during range evolution in this obligate mutualism.

Phylogenetic patterns of ant-fungus associations indicate that farming strategies, not only a superior fungal cultivar, explain the ecological success of leafcutter ants.

To elucidate fungicultural specializations contributing to ecological dominance of leafcutter ants, we estimate the phylogeny of fungi cultivated by fungus-growing (attine) ants, including fungal cultivars from (i) the entire leafcutter range from southern South America to southern North America, (ii) all higher-attine ant lineages (leafcutting genera Atta, Acromyrmex; nonleafcutting genera Trachymyrmex, Sericomyrmex) and (iii) all lower-attine lineages. Higher-attine fungi form two clades, Clade-A fungi (Leucocoprinus gongylophorus, formerly Attamyces) previously thought to be cultivated only by leafcutter ants, and a sister clade, Clade-B fungi, previously thought to be cultivated only by Trachymyrmex and Sericomyrmex ants. Contradicting this traditional view, we find that (i) leafcutter ants are not specialized to cultivate only Clade-A fungi because some leafcutter species ranging across South America cultivate Clade-B fungi; (ii) Trachymyrmex ants are not specialized to cultivate only Clade-B fungi because some Trachymyrmex species cultivate Clade-A fungi and other Trachymyrmex species cultivate fungi known so far only from lower-attine ants; (iii) in some locations, single higher-attine ant species or closely related cryptic species cultivate both Clade-A and Clade-B fungi; and (iv) ant-fungus co-evolution among higher-attine mutualisms is therefore less specialized than previously thought. Sympatric leafcutter ants can be ecologically dominant when cultivating either Clade-A or Clade-B fungi, sustaining with either cultivar-type huge nests that command large foraging territories; conversely, sympatric Trachymyrmex ants cultivating either Clade-A or Clade-B fungi can be locally abundant without achieving the ecological dominance of leafcutter ants. Ecological dominance of leafcutter ants therefore does not depend primarily on specialized fungiculture of L. gongylophorus (Clade-A), but must derive from ant-fungus synergisms and unique ant adaptations.

Biogeography of mutualistic fungi cultivated by leafcutter ants.

Leafcutter ants propagate co-evolving fungi for food. The nearly 50 species of leafcutter ants (Atta, Acromyrmex) range from Argentina to the United States, with the greatest species diversity in southern South America. We elucidate the biogeography of fungi cultivated by leafcutter ants using DNA sequence and microsatellite-marker analyses of 474 cultivars collected across the leafcutter range. Fungal cultivars belong to two clades (Clade-A and Clade-B). The dominant and widespread Clade-A cultivars form three genotype clusters, with their relative prevalence corresponding to southern South America, northern South America, Central and North America. Admixture between Clade-A populations supports genetic exchange within a single species, Leucocoprinus gongylophorus. Some leafcutter species that cut grass as fungicultural substrate are specialized to cultivate Clade-B fungi, whereas leafcutters preferring dicot plants appear specialized on Clade-A fungi. Cultivar sharing between sympatric leafcutter species occurs frequently such that cultivars of Atta are not distinct from those of Acromyrmex. Leafcutters specialized on Clade-B fungi occur only in South America. Diversity of Clade-A fungi is greatest in South America, but minimal in Central and North America. Maximum cultivar diversity in South America is predicted by the Kusnezov-Fowler hypothesis that leafcutter ants originated in subtropical South America and only dicot-specialized leafcutter ants migrated out of South America, but the cultivar diversity becomes also compatible with a recently proposed hypothesis of a Central American origin by postulating that leafcutter ants acquired novel cultivars many times from other nonleafcutter fungus-growing ants during their migrations from Central America across South America. We evaluate these biogeographic hypotheses in the light of estimated dates for the origins of leafcutter ants and their cultivars.