Airborne DNA reveals predictable spatial and seasonal dynamics of fungi.

Fungi are among the most diverse and ecologically important kingdoms in life. However, the distributional ranges of fungi remain largely unknown as do the ecological mechanisms that shape their distributions1,2. To provide an integrated view of the spatial and seasonal dynamics of fungi, we implemented a globally distributed standardized aerial sampling of fungal spores3. The vast majority of operational taxonomic units were detected within only one climatic zone, and the spatiotemporal patterns of species richness and community composition were mostly explained by annual mean air temperature. Tropical regions hosted the highest fungal diversity except for lichenized, ericoid mycorrhizal and ectomycorrhizal fungi, which reached their peak diversity in temperate regions. The sensitivity in climatic responses was associated with phylogenetic relatedness, suggesting that large-scale distributions of some fungal groups are partially constrained by their ancestral niche. There was a strong phylogenetic signal in seasonal sensitivity, suggesting that some groups of fungi have retained their ancestral trait of sporulating for only a short period. Overall, our results show that the hyperdiverse kingdom of fungi follows globally highly predictable spatial and temporal dynamics, with seasonality in both species richness and community composition increasing with latitude. Our study reports patterns resembling those described for other major groups of organisms, thus making a major contribution to the long-standing debate on whether organisms with a microbial lifestyle follow the global biodiversity paradigms known for macroorganisms4,5.

Experimental evidence that root-associated fungi improve plant growth at high altitude.

Unravelling how species communities change along environmental gradients requires a dual understanding: the direct responses of the species to their abiotic surroundings and the indirect variation of these responses through biotic interactions. Here, we focus on the interactive relationships between plants and their symbiotic root-associated fungi (RAF) along stressful abiotic gradients. We investigate whether variations in RAF community composition along altitudinal gradients influence plant growth at high altitudes, where both plants and fungi face harsher abiotic conditions. We established a translocation experiment between pairs of Bistorta vivipara populations across altitudinal gradients. To separate the impact of shifting fungal communities from the overall influence of changing abiotic conditions, we used a root barrier to prevent new colonization by RAF following translocation. To characterize the RAF communities, we applied DNA barcoding to the root samples. Through the utilization of joint species distribution modelling, we assessed the relationship between changes in plant functional traits resulting from experimental treatments and the corresponding changes in the RAF communities. Our findings indicate that RAF communities influence plant responses to stressful abiotic conditions. Plants translocated from low to high altitudes grew more when they were able to associate with the resident high-altitude RAF compared to those plants that were not allowed to associate with the resident RAF. We conclude that interactions with RAF impact how plants respond to stressful abiotic conditions. Our results provide experimental support that interactions with RAF improve plant stress tolerance to altitudinal stressors such as colder temperatures and less nutrient availability.

Spatial cumulant models enable spatially informed treatment strategies and analysis of local interactions in cancer systems.

Theoretical and applied cancer studies that use individual-based models (IBMs) have been limited by the lack of a mathematical formulation that enables rigorous analysis of these models. However, spatial cumulant models (SCMs), which have arisen from theoretical ecology, describe population dynamics generated by a specific family of IBMs, namely spatio-temporal point processes (STPPs). SCMs are spatially resolved population models formulated by a system of differential equations that approximate the dynamics of two STPP-generated summary statistics: first-order spatial cumulants (densities), and second-order spatial cumulants (spatial covariances). We exemplify how SCMs can be used in mathematical oncology by modelling theoretical cancer cell populations comprising interacting growth factor-producing and non-producing cells. To formulate model equations, we use computational tools that enable the generation of STPPs, SCMs and mean-field population models (MFPMs) from user-defined model descriptions (Cornell et al. Nat Commun 10:4716, 2019). To calculate and compare STPP, SCM and MFPM-generated summary statistics, we develop an application-agnostic computational pipeline. Our results demonstrate that SCMs can capture STPP-generated population density dynamics, even when MFPMs fail to do so. From both MFPM and SCM equations, we derive treatment-induced death rates required to achieve non-growing cell populations. When testing these treatment strategies in STPP-generated cell populations, our results demonstrate that SCM-informed strategies outperform MFPM-informed strategies in terms of inhibiting population growths. We thus demonstrate that SCMs provide a new framework in which to study cell-cell interactions, and can be used to describe and perturb STPP-generated cell population dynamics. We, therefore, argue that SCMs can be used to increase IBMs' applicability in cancer research.

Effects of landscape and distance in automatic audio based bird species identification.

The present work focuses on how the landscape and distance between a bird and an audio recording unit affect automatic species identification. Moreover, it is shown that automatic species identification can be improved by taking into account the effects of landscape and distance. The proposed method uses measurements of impulse responses between the sound source and the recorder. These impulse responses, characterizing the effect of a landscape, can be measured in the real environment, after which they can be convolved with any number of recorded bird sounds to modify an existing set of bird sound recordings. The method is demonstrated using autonomous recording units on an open field and in two different types of forests, varying the distance between the sound source and the recorder. Species identification accuracy improves significantly when the landscape and distance effect is taken into account when building the classification model. The method is demonstrated using bird sounds, but the approach is applicable to other animal and non-animal vocalizations as well.

Alternative developmental and transcriptomic responses to host plant water limitation in a butterfly metapopulation.

Predicting how climate change affects biotic interactions poses a challenge. Plant-insect herbivore interactions are particularly sensitive to climate change, as climate-induced changes in plant quality cascade into the performance of insect herbivores. Whereas the immediate survival of herbivore individuals depends on plastic responses to climate change-induced nutritional stress, long-term population persistence via evolutionary adaptation requires genetic variation for these responses. To assess the prospects for population persistence under climate change, it is therefore crucial to characterize response mechanisms to climate change-induced stressors, and quantify their variability in natural populations. Here, we test developmental and transcriptomic responses to water limitation-induced host plant quality change in a Glanville fritillary butterfly (Melitaea cinxia) metapopulation. We combine nuclear magnetic resonance spectroscopy on the plant metabolome, larval developmental assays and an RNA sequencing analysis of the larval transcriptome. We observed that responses to feeding on water-limited plants, in which amino acids and aromatic compounds are enriched, showed marked variation within the metapopulation, with individuals of some families performing better on control and others on water-limited plants. The transcriptomic responses were concordant with the developmental responses: families exhibiting opposite developmental responses also produced opposite transcriptomic responses (e.g. in growth-associated transcripts). The divergent responses in both larval development and transcriptome are associated with differences between families in amino acid catabolism and storage protein production. The results reveal intrapopulation variability in plasticity, suggesting that the Finnish M. cinxia metapopulation harbours potential for buffering against drought-induced changes in host plant quality.

Accounting for environmental variation in co-occurrence modelling reveals the importance of positive interactions in root-associated fungal communities.

Understanding the role of interspecific interactions in shaping ecological communities is one of the central goals in community ecology. In fungal communities, measuring interspecific interactions directly is challenging because these communities are composed of large numbers of species, many of which are unculturable. An indirect way of assessing the role of interspecific interactions in determining community structure is to identify the species co-occurrences that are not constrained by environmental conditions. In this study, we investigated co-occurrences among root-associated fungi, asking whether fungi co-occur more or less strongly than expected based on the environmental conditions and the host plant species examined. We generated molecular data on root-associated fungi of five plant species evenly sampled along an elevational gradient at a high arctic site. We analysed the data using a joint species distribution modelling approach that allowed us to identify those co-occurrences that could be explained by the environmental conditions and the host plant species, as well as those co-occurrences that remained unexplained and thus more probably reflect interactive associations. Our results indicate that not only negative but also positive interactions play an important role in shaping microbial communities in arctic plant roots. In particular, we found that mycorrhizal fungi are especially prone to positively co-occur with other fungal species. Our results bring new understanding to the structure of arctic interaction networks by suggesting that interactions among root-associated fungi are predominantly positive.

Effect of wet storage conditions on potato tuber transcriptome, phytohormones and growth.

BACKGROUND: Stored potato (Solanum tuberosum L.) tubers are sensitive to wet conditions that can cause rotting in long-term storage. To study the effect of water on the tuber surface during storage, microarray analysis, RNA-Seq profiling, qRT-PCR and phytohormone measurements were performed to study gene expression and hormone content in wet tubers incubated at two temperatures: 4 °C and 15 °C. The growth of the plants was also observed in a greenhouse after the incubation of tubers in wet conditions. RESULTS: Wet conditions induced a low-oxygen response, suggesting reduced oxygen availability in wet tubers at both temperatures when compared to that in the corresponding dry samples. Wet conditions induced genes coding for heat shock proteins, as well as proteins involved in fermentative energy production and defense against reactive oxygen species (ROS), which are transcripts that have been previously associated with low-oxygen stress in hypoxic or anoxic conditions. Wet treatment also induced senescence-related gene expression and genes involved in cell wall loosening, but downregulated genes encoding protease inhibitors and proteins involved in chloroplast functions and in the biosynthesis of secondary metabolites. Many genes involved in the production of phytohormones and signaling were also affected by wet conditions, suggesting altered regulation of growth by wet conditions. Hormone measurements after incubation showed increased salicylic acid (SA), abscisic acid (ABA) and auxin (IAA) concentrations as well as reduced production of jasmonate 12-oxo-phytodienoic acid (OPDA) in wet tubers. After incubation in wet conditions, the tubers produced fewer stems and more roots compared to controls incubated in dry conditions. CONCLUSIONS: In wet conditions, tubers invest in ROS protection and defense against the abiotic stress caused by reduced oxygen due to excessive water. Changes in ABA, SA and IAA that are antagonistic to jasmonates affect growth and defenses, causing induction of root growth and rendering tubers susceptible to necrotrophic pathogens. Water on the tuber surface may function as a signal for growth, similar to germination of seeds.

Scaling up the effects of inbreeding depression from individuals to metapopulations.

Inbreeding is common in nature, and many laboratory studies have documented that inbreeding depression can reduce the fitness of individuals. Demonstrating the consequences of inbreeding depression on the growth and persistence of populations is more challenging because populations are often regulated by density- or frequency-dependent selection and influenced by demographic and environmental stochasticity. A few empirical studies have shown that inbreeding depression can increase extinction risk of local populations. The importance of inbreeding depression at the metapopulation level has been conjectured based on population-level studies but has not been evaluated. We quantified the impact of inbreeding depression affecting the fitness of individuals on metapopulation persistence in heterogeneous habitat networks of different sizes and habitat configuration in a context of natural butterfly metapopulations. We developed a spatial individual-based simulation model of metapopulations with explicit genetics. We used Approximate Bayesian Computation to fit the model to extensive demographic, genetic and life-history data available for the well-studied Glanville fritillary butterfly (Melitaea cinxia) metapopulations in the Åland islands in SW Finland. We compared 18 semi-independent habitat networks differing in size and fragmentation. The results show that inbreeding is more frequent in small habitat networks, and consequently, inbreeding depression elevates extinction risks in small metapopulations. Metapopulation persistence and neutral genetic diversity maintained in the metapopulations increase with the total habitat amount in and mean patch size of habitat networks. Dispersal and mating behaviour interact with landscape structure to determine how likely it is to encounter kin while looking for mates. Inbreeding depression can decrease the viability of small metapopulations even when they are strongly influenced by stochastic extinction-colonization dynamics and density-dependent selection. The findings from this study support that genetic factors, in addition to demographic factors, can contribute to extinctions of small local populations and also of metapopulations.

BARCOSEL: a tool for selecting an optimal barcode set for high-throughput sequencing.

BACKGROUND: Current high-throughput sequencing platforms provide capacity to sequence multiple samples in parallel. Different samples are labeled by attaching a short sample specific nucleotide sequence, barcode, to each DNA molecule prior pooling them into a mix containing a number of libraries to be sequenced simultaneously. After sequencing, the samples are binned by identifying the barcode sequence within each sequence read. In order to tolerate sequencing errors, barcodes should be sufficiently apart from each other in sequence space. An additional constraint due to both nucleotide usage and basecalling accuracy is that the proportion of different nucleotides should be in balance in each barcode position. The number of samples to be mixed in each sequencing run may vary and this introduces a problem how to select the best subset of available barcodes at sequencing core facility for each sequencing run. There are plenty of tools available for de novo barcode design, but they are not suitable for subset selection. RESULTS: We have developed a tool which can be used for three different tasks: 1) selecting an optimal barcode set from a larger set of candidates, 2) checking the compatibility of user-defined set of barcodes, e.g. whether two or more libraries with existing barcodes can be combined in a single sequencing pool, and 3) augmenting an existing set of barcodes. In our approach the selection process is formulated as a minimization problem. We define the cost function and a set of constraints and use integer programming to solve the resulting combinatorial problem. Based on the desired number of barcodes to be selected and the set of candidate sequences given by user, the necessary constraints are automatically generated and the optimal solution can be found. The method is implemented in C programming language and web interface is available at http://ekhidna2.biocenter.helsinki.fi/barcosel . CONCLUSIONS: Increasing capacity of sequencing platforms raises the challenge of mixing barcodes. Our method allows the user to select a given number of barcodes among the larger existing barcode set so that both sequencing errors are tolerated and the nucleotide balance is optimized. The tool is easy to access via web browser.

Animal Sound Identifier (ASI): software for automated identification of vocal animals.

Automated audio recording offers a powerful tool for acoustic monitoring schemes of bird, bat, frog and other vocal organisms, but the lack of automated species identification methods has made it difficult to fully utilise such data. We developed Animal Sound Identifier (ASI), a MATLAB software that performs probabilistic classification of species occurrences from field recordings. Unlike most previous approaches, ASI locates training data directly from the field recordings and thus avoids the need of pre-defined reference libraries. We apply ASI to a case study on Amazonian birds, in which we classify the vocalisations of 14 species in 194 504 one-minute audio segments using in total two weeks of expert time to construct, parameterise, and validate the classification models. We compare the classification performance of ASI (with training templates extracted automatically from field data) to that of monitoR (with training templates extracted manually from the Xeno-Canto database), the results showing ASI to have substantially higher recall and precision rates.

Protax-fungi: a web-based tool for probabilistic taxonomic placement of fungal internal transcribed spacer sequences.

Incompleteness of reference sequence databases and unresolved taxonomic relationships complicates taxonomic placement of fungal sequences. We developed Protax-fungi, a general tool for taxonomic placement of fungal internal transcribed spacer (ITS) sequences, and implemented it into the PlutoF platform of the UNITE database for molecular identification of fungi. With empirical data on root- and wood-associated fungi, Protax-fungi reliably identified (with at least 90% identification probability) the majority of sequences to the order level but only around one-fifth of them to the species level, reflecting the current limited coverage of the databases. Protax-fungi outperformed the Sintax and Rdb classifiers in terms of increased accuracy and decreased calibration error when applied to data on mock communities representing species groups with poor sequence database coverage. We applied Protax-fungi to examine the internal consistencies of the Index Fungorum and UNITE databases. This revealed inconsistencies in the taxonomy database as well as mislabelling and sequence quality problems in the reference database. The according improvements were implemented in both databases. Protax-fungi provides a robust tool for performing statistically reliable identifications of fungi in spite of the incompleteness of extant reference sequence databases and unresolved taxonomic relationships.

Unbiased probabilistic taxonomic classification for DNA barcoding.

MOTIVATION: When targeted to a barcoding region, high-throughput sequencing can be used to identify species or operational taxonomical units from environmental samples, and thus to study the diversity and structure of species communities. Although there are many methods which provide confidence scores for assigning taxonomic affiliations, it is not straightforward to translate these values to unbiased probabilities. We present a probabilistic method for taxonomical classification (PROTAX) of DNA sequences. Given a pre-defined taxonomical tree structure that is partially populated by reference sequences, PROTAX decomposes the probability of one to the set of all possible outcomes. PROTAX accounts for species that are present in the taxonomy but that do not have reference sequences, the possibility of unknown taxonomical units, as well as mislabeled reference sequences. PROTAX is based on a statistical multinomial regression model, and it can utilize any kind of sequence similarity measures or the outputs of other classifiers as predictors. RESULTS: We demonstrate the performance of PROTAX by using as predictors the output from BLAST, the phylogenetic classification software TIPP, and the RDP classifier. We show that PROTAX improves the predictions of the baseline implementations of TIPP and RDP classifiers, and that it is able to combine complementary information provided by BLAST and TIPP, resulting in accurate and unbiased classifications even with very challenging cases such as 50% mislabeling of reference sequences. AVAILABILITY AND IMPLEMENTATION: Perl/R implementation of PROTAX is available at http://www.helsinki.fi/science/metapop/Software.htm CONTACT: panu.somervuo@helsinki.fi SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SANSparallel: interactive homology search against Uniprot.

Proteins evolve by mutations and natural selection. The network of sequence similarities is a rich source for mining homologous relationships that inform on protein structure and function. There are many servers available to browse the network of homology relationships but one has to wait up to a minute for results. The SANSparallel webserver provides protein sequence database searches with immediate response and professional alignment visualization by third-party software. The output is a list, pairwise alignment or stacked alignment of sequence-similar proteins from Uniprot, UniRef90/50, Swissprot or Protein Data Bank. The stacked alignments are viewed in Jalview or as sequence logos. The database search uses the suffix array neighborhood search (SANS) method, which has been re-implemented as a client-server, improved and parallelized. The method is extremely fast and as sensitive as BLAST above 50% sequence identity. Benchmarks show that the method is highly competitive compared to previously published fast database search programs: UBLAST, DIAMOND, LAST, LAMBDA, RAPSEARCH2 and BLAT. The web server can be accessed interactively or programmatically at http://ekhidna2.biocenter.helsinki.fi/cgi-bin/sans/sans.cgi. It can be used to make protein functional annotation pipelines more efficient, and it is useful in interactive exploration of the detailed evidence supporting the annotation of particular proteins of interest.

Differential isoform expression and selective muscle involvement in muscular dystrophies.

Despite the expression of the mutated gene in all muscles, selective muscles are involved in genetic muscular dystrophies. Different muscular dystrophies show characteristic patterns of fatty degenerative changes by muscle imaging, even to the extent that the patterns have been used for diagnostic purposes. However, the underlying molecular mechanisms explaining the selective involvement of muscles are not known. To test the hypothesis that different muscles may express variable amounts of different isoforms of muscle genes, we applied a custom-designed exon microarray containing probes for 57 muscle-specific genes to assay the transcriptional profiles in sets of human adult lower limb skeletal muscles. Quantitative real-time PCR and whole transcriptome sequencing were used to further analyze the results. Our results demonstrate significant variations in isoform and gene expression levels in anatomically different muscles. Comparison of the known patterns of selective involvement of certain muscles in two autosomal dominant titinopathies and one autosomal dominant myosinopathy, with the isoform and gene expression results, shows a correlation between the specific muscles involved and significant differences in the level of expression of the affected gene and exons in these same muscles compared with some other selected muscles. Our results suggest that differential expression levels of muscle genes and isoforms are one determinant in the selectivity of muscle involvement in muscular dystrophies.

Flight-induced changes in gene expression in the Glanville fritillary butterfly.

Insect flight is one of the most energetically demanding activities in the animal kingdom, yet for many insects flight is necessary for reproduction and foraging. Moreover, dispersal by flight is essential for the viability of species living in fragmented landscapes. Here, working on the Glanville fritillary butterfly (Melitaea cinxia), we use transcriptome sequencing to investigate gene expression changes caused by 15 min of flight in two contrasting populations and the two sexes. Male butterflies and individuals from a large metapopulation had significantly higher peak flight metabolic rate (FMR) than female butterflies and those from a small inbred population. In the pooled data, FMR was significantly positively correlated with genome-wide heterozygosity, a surrogate of individual inbreeding. The flight experiment changed the expression level of 1513 genes, including genes related to major energy metabolism pathways, ribosome biogenesis and RNA processing, and stress and immune responses. Males and butterflies from the population with high FMR had higher basal expression of genes related to energy metabolism, whereas females and butterflies from the small population with low FMR had higher expression of genes related to ribosome/RNA processing and immune response. Following the flight treatment, genes related to energy metabolism were generally down-regulated, while genes related to ribosome/RNA processing and immune response were up-regulated. These results suggest that common molecular mechanisms respond to flight and can influence differences in flight metabolic capacity between populations and sexes.

Protein secretome of moss plants (Physcomitrella patens) with emphasis on changes induced by a fungal elicitor.

Studies on extracellular proteins (ECPs) contribute to understanding of the multifunctional nature of apoplast. Unlike vascular plants (tracheophytes), little information about ECPs is available from nonvascular plants, such as mosses (bryophytes). In this study, moss plants (Physcomitrella patens) were grown in liquid culture and treated with chitosan, a water-soluble form of chitin that occurs in cell walls of fungi and insects and elicits pathogen defense in plants. ECPs released to the culture medium were compared between chitosan-treated and nontreated control cultures using quantitative mass spectrometry (Orbitrap) and 2-DE-LC-MS/MS. Over 400 secreted proteins were detected, of which 70% were homologous to ECPs reported in tracheophyte secretomes. Bioinformatics analyses using SignalP and SecretomeP predicted classical signal peptides for secretion (37%) or leaderless secretion (27%) for most ECPs of P. patens, but secretion of the remaining proteins (36%) could not be predicted using bioinformatics. Cultures treated with chitosan contained 72 proteins not found in untreated controls, whereas 27 proteins found in controls were not detected in chitosan-treated cultures. Pathogen defense-related proteins dominated in the secretome of P. patens, as reported in tracheophytes. These results advance knowledge on protein secretomes of plants by providing a comprehensive account of ECPs of a bryophyte.

The cold-induced two-component system CBO0366/CBO0365 regulates metabolic pathways with novel roles in group I Clostridium botulinum ATCC 3502 cold tolerance.

The two-component system CBO0366/CBO0365 was recently demonstrated to have a role in cold tolerance of group I Clostridium botulinum ATCC 3502. The mechanisms under its control, ultimately resulting in increased sensitivity to low temperature, are unknown. A transcriptomic analysis with DNA microarrays was performed to identify the differences in global gene expression patterns of the wild-type ATCC 3502 and a derivative mutant with insertionally inactivated cbo0365 at 37 and 15°C. Altogether, 150 or 141 chromosomal coding sequences (CDSs) were found to be differently expressed in the cbo0365 mutant at 37 or 15°C, respectively, and thus considered to be under the direct or indirect transcriptional control of the response regulator CBO0365. Of the differentially expressed CDSs, expression of 141 CDSs was similarly affected at both temperatures investigated, suggesting that the putative CBO0365 regulon was practically not affected by temperature. The regulon involved genes related to acetone-butanol-ethanol (ABE) fermentation, motility, arsenic resistance, and phosphate uptake and transport. Deteriorated growth at 17°C was observed for mutants with disrupted ABE fermentation pathway components (crt, bcd, bdh, and ctfA), arsenic detoxifying machinery components (arsC and arsR), or phosphate uptake mechanism components (phoT), suggesting roles for these mechanisms in cold tolerance of group I C. botulinum. Electrophoretic mobility shift assays showed recombinant CBO0365 to bind to the promoter regions of crt, arsR, and phoT, as well as to the promoter region of its own operon, suggesting direct DNA-binding transcriptional activation or repression as a means for CBO0365 in regulating these operons. The results provide insight to the mechanisms group I C. botulinum utilizes in coping with cold.

PROTAX-GPU: a scalable probabilistic taxonomic classification system for DNA barcodes.

DNA-based identification is vital for classifying biological specimens, yet methods to quantify the uncertainty of sequence-based taxonomic assignments are scarce. Challenges arise from noisy reference databases, including mislabelled entries and missing taxa. PROTAX addresses these issues with a probabilistic approach to taxonomic classification, advancing on methods that rely solely on sequence similarity. It provides calibrated probabilistic assignments to a partially populated taxonomic hierarchy, accounting for taxa that lack references and incorrect taxonomic annotation. While effective on smaller scales, global application of PROTAX necessitates substantially larger reference libraries, a goal previously hindered by computational barriers. We introduce PROTAX-GPU, a scalable algorithm capable of leveraging the global Barcode of Life Data System (>14 million specimens) as a reference database. Using graphics processing units (GPU) to accelerate similarity and nearest-neighbour operations and the JAX library for Python integration, we achieve over a 1000 × speedup compared with the central processing unit (CPU)-based implementation without compromising PROTAX's key benefits. PROTAX-GPU marks a significant stride towards real-time DNA barcoding, enabling quicker and more efficient species identification in environmental assessments. This capability opens up new avenues for real-time monitoring and analysis of biodiversity, advancing our ability to understand and respond to ecological dynamics. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Global Spore Sampling Project: A global, standardized dataset of airborne fungal DNA.

Novel methods for sampling and characterizing biodiversity hold great promise for re-evaluating patterns of life across the planet. The sampling of airborne spores with a cyclone sampler, and the sequencing of their DNA, have been suggested as an efficient and well-calibrated tool for surveying fungal diversity across various environments. Here we present data originating from the Global Spore Sampling Project, comprising 2,768 samples collected during two years at 47 outdoor locations across the world. Each sample represents fungal DNA extracted from 24 m3 of air. We applied a conservative bioinformatics pipeline that filtered out sequences that did not show strong evidence of representing a fungal species. The pipeline yielded 27,954 species-level operational taxonomic units (OTUs). Each OTU is accompanied by a probabilistic taxonomic classification, validated through comparison with expert evaluations. To examine the potential of the data for ecological analyses, we partitioned the variation in species distributions into spatial and seasonal components, showing a strong effect of the annual mean temperature on community composition.

Alternative sigma factor σE has an important role in stress tolerance of Yersinia pseudotuberculosis IP32953.

Yersinia pseudotuberculosis is an important pathogen that probably survives well in the modern food chain. However, little is known about the mechanisms that allow the growth of this pathogen in foods under stress conditions. The expression of rpoE encoding σ(E) was defined by quantitative real-time reverse transcription-PCR. Expression of rpoE was induced at 3°C, 37°C, and 42°C, under exposure to 3% NaCl, 3% ethanol, or high and low pH, in relation to its expression at the optimum growth temperature of 28°C of Y. pseudotuberculosis. Mutation of rpoE either impaired or abolished growth under stresses caused by low or high temperature, low pH, and ethanol. In addition, the growth temperature range of the mutant was significantly diminished compared to that of the wild-type strain IP32953. The results were confirmed with complementation of the mutant. Thus, σ(E) plays a significant role in the stress tolerance of Y. pseudotuberculosis IP32953 and probably contributes to the survival of this pathogen in the food chain.