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- Biodiversität und Klima Forschungszentrum (BiK-F) (16) (remove)
Trypanosoma cruzi, the causative agent of Chagas disease (American trypanosomiasis), colonizes the intestinal tract of triatomines. Triatomine bugs act as vectors in the life cycle of the parasite and transmit infective parasite stages to animals and humans. Contact of the vector with T. cruzi alters its intestinal microbial composition, which may also affect the associated metabolic patterns of the insect. Earlier studies suggest that the complexity of the triatomine fecal metabolome may play a role in vector competence for different T. cruzi strains. Using high-resolution mass spectrometry and supervised machine learning, we aimed to detect differences in the intestinal metabolome of the triatomine Rhodnius prolixus and predict whether the insect had been exposed to T. cruzi or not based solely upon their metabolic profile. We were able to predict the exposure status of R. prolixus to T. cruzi with accuracies of 93.6%, 94.2% and 91.8% using logistic regression, a random forest classifier and a gradient boosting machine model, respectively. We extracted the most important features in producing the models and identified the major metabolites which assist in positive classification. This work highlights the complex interactions between triatomine vector and parasite including effects on the metabolic signature of the insect.
This study was performed to identify Peronosclerospora species found in Indonesia based on sequence analysis of the cox2 gene. In addition, sequence data in total, 26 isolates of Peronosclerospora were investigated in this study. They were obtained from 7 provinces in Indonesia, namely Lampung, Jawa Timur, Jawa Barat, Sumatera Utara, Jawa Tengah, Yogyakarta, and Sulawesi Selatan. Sequence analysis of cox2 and phylogenetic inference were performed on all the 26 isolates. A set of primers developed in this study, PCOX2F and PCOX2R, was used for PCR amplification. Phylogenetic analyses showed that all the Indonesian isolates were divided into two groups. Group I contained 13 isolates; 9 isolates obtained from Lampung, 3 isolates from Sumatera Utara, and 1 isolate from Jawa Barat. Group II consisted of 13 isolates; 7 isolates from Jawa Timur, 2 isolates from Jawa Tengah, 1 isolate from Yogyakarta, and 3 isolates from Sulawesi Selatan. All the members of group I clustered with the ex-type sequence of P. australiensis. Meanwhile, all members of Group II formed the sister clade of isolates obtained from Timor-Leste and may represent P. maydis.
Kálmán Vánky (15th of June 1930–18th of October 2021) was arguably the most prolific researcher of smut fungi so far. He published more than 1000 taxonomic novelties, and crowned his outstanding oeuvre with the most comprehensive monograph of the smut fungi (Smut Fungi of the World) written to date.
he most basic behavioural states of animals can be described as active or passive. While high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which a combination of automatic radiotracking and machine learning is used to distinguish between active and passive behaviour in small vertebrates fitted with lightweight transmitters (<0.4 g).
We used a dataset containing >3 million signals from very-high-frequency (VHF) telemetry from two forest-dwelling bat species (Myotis bechsteinii [n = 52] and Nyctalus leisleri [n = 20]) to train and test a random forest model in assigning either active or passive behaviour to VHF-tagged individuals. The generalisability of the model was demonstrated by recording and classifying the behaviour of tagged birds and by simulating the effect of different activity levels with the help of humans carrying transmitters. The model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F1 0.96–0.98).
We provide an ecological case-study demonstrating the potential of this automated monitoring tool. We used the trained models to compare differences in the daily activity patterns of two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that subtle differences in the timing of species' activity can be distinguished using our method.
Our approach can classify VHF-signal patterns into fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radiotracking method, we provide the trained random forest models together with an R package that includes all necessary data processing functionalities. In combination with state-of-the-art open-source automated radiotracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.
The most basic behavioural states of animals can be described as active or passive. However, while high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which the automated VHF radio-tracking of small vertebrates fitted with lightweight transmitters (< 0.2 g) is used to distinguish between active and passive behavioural states.
A dataset containing > 3 million VHF signals was used to train and test a random forest model in the assignment of either active or passive behaviour to individuals from two forest-dwelling bat species (Myotis bechsteinii (n = 50) and Nyctalus leisleri (n = 20)). The applicability of the model to other taxonomic groups was demonstrated by recording and classifying the behaviour of a tagged bird and by simulating the effect of different types of vertebrate activity with the help of humans carrying transmitters. The random forest model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F-score 0.96–0.98).
The utility of the model in tackling ecologically relevant questions was demonstrated in a study of the differences in the daily activity patterns of the two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that significant differences in the timing of species activity according to ecological preferences or seasonality can be distinguished using our method.
Our approach enables the assignment of VHF signal patterns to fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radio-tracking method, we provide the trained random forest models together with an R-package that includes all necessary data-processing functionalities. In combination with state-of-the-art open-source automated radio-tracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.
Vampire bats are the only mammals that feed exclusively on blood. To uncover genomic changes associated with this dietary adaptation, we generated a haplotype-resolved genome of the common vampire bat and screened 27 bat species for genes that were specifically lost in the vampire bat lineage. We found previously unknown gene losses that relate to reduced insulin secretion (FFAR1 and SLC30A8), limited glycogen stores (PPP1R3E), and a unique gastric physiology (CTSE). Other gene losses likely reflect the biased nutrient composition (ERN2 and CTRL) and distinct pathogen diversity of blood (RNASE7) and predict the complete lack of cone-based vision in these strictly nocturnal bats (PDE6H and PDE6C). Notably, REP15 loss likely helped vampire bats adapt to high dietary iron levels by enhancing iron excretion, and the loss of CYP39A1 could have contributed to their exceptional cognitive abilities. These findings enhance our understanding of vampire bat biology and the genomic underpinnings of adaptations to blood feeding.
The European Beech is the dominant climax tree in most regions of Central Europe and valued for its ecological versatility and hardwood timber. Even though a draft genome has been published recently, higher resolution is required for studying aspects of genome architecture and recombination. Here, we present a chromosome-level assembly of the more than 300 year-old reference individual, Bhaga, from the Kellerwald-Edersee National Park (Germany). Its nuclear genome of 541 Mb was resolved into 12 chromosomes varying in length between 28 and 73 Mb. Multiple nuclear insertions of parts of the chloroplast genome were observed, with one region on chromosome 11 spanning more than 2 Mb which fragments up to 54,784 bp long and covering the whole chloroplast genome were inserted randomly. Unlike in Arabidopsis thaliana, ribosomal cistrons are present in Fagus sylvatica only in four major regions, in line with FISH studies. On most assembled chromosomes, telomeric repeats were found at both ends, while centromeric repeats were found to be scattered throughout the genome apart from their main occurrence per chromosome. The genome-wide distribution of SNPs was evaluated using a second individual from Jamy Nature Reserve (Poland). SNPs, repeat elements and duplicated genes were unevenly distributed in the genomes, with one major anomaly on chromosome 4. The genome presented here adds to the available highly resolved plant genomes and we hope it will serve as a valuable basis for future research on genome architecture and for understanding the past and future of European Beech populations in a changing climate.
Motivation Expert curation to differentiate between functionally diverged homologs and those that may still share a similar function routinely relies on the visual interpretation of domain architecture changes. However, the size of contemporary data sets integrating homologs from hundreds to thousands of species calls for alternate solutions. Scoring schemes to evaluate domain architecture similarities can help to automatize this procedure, in principle. But existing schemes are often too simplistic in the similarity assessment, many require an a-priori resolution of overlapping domain annotations, and those that allow overlaps to extend the set of annotations sources cannot account for redundant annotations. As a consequence, the gap between the automated similarity scoring and the similarity assessment based on visual architecture comparison is still too wide to make the integration of both approaches meaningful.
Results Here, we present FAS, a scoring system for the comparison of multi-layered feature architectures integrating information from a broad spectrum of annotation sources. Feature architectures are represented as directed acyclic graphs, and redundancies are resolved in the course of comparison using a score maximization algorithm. A benchmark using more than 10,000 human-yeast ortholog pairs reveals that FAS consistently outperforms existing scoring schemes. Using three examples, we show how automated architecture similarity assessments can be routinely applied in the benchmarking of orthology assignment software, in the identification of functionally diverged orthologs, and in the identification of entries in protein collections that most likely stem from a faulty gene prediction.
Molluscs are the second most species-rich phylum in the animal kingdom, yet only 11 genomes of this group have been published so far. Here, we present the draft genome sequence of the pulmonate freshwater snail Radix auricularia. Six whole genome shotgun libraries with different layouts were sequenced. The resulting assembly comprises 4,823 scaffolds with a cumulative length of 910 Mb and an overall read coverage of 72×. The assembly contains 94.6% of a metazoan core gene collection, indicating an almost complete coverage of the coding fraction. The discrepancy of ∼690 Mb compared with the estimated genome size of R. auricularia (1.6 Gb) results from a high repeat content of 70% mainly comprising DNA transposons. The annotation of 17,338 protein coding genes was supported by the use of publicly available transcriptome data. This draft will serve as starting point for further genomic and population genetic research in this scientifically important phylum.
Combinatorial CRISPR-Cas screens have advanced the mapping of genetic interactions, but their experimental scale limits the number of targetable gene combinations. Here, we describe 3Cs multiplexing, a rapid and scalable method to generate highly diverse and uniformly distributed combinatorial CRISPR libraries. We demonstrate that the library distribution skew is the critical determinant of its required screening coverage. By circumventing iterative cloning of PCR-amplified oligonucleotides, 3Cs multiplexing facilitates the generation of combinatorial CRISPR libraries with low distribution skews. We show that combinatorial 3Cs libraries can be screened with minimal coverages, reducing associated efforts and costs at least 10-fold. We apply a 3Cs multiplexing library targeting 12,736 autophagy gene combinations with 247,032 paired gRNAs in viability and reporter-based enrichment screens. In the viability screen, we identify, among others, the synthetic lethal WDR45B-PIK3R4 and the proliferation-enhancing ATG7-KEAP1 genetic interactions. In the reporter-based screen, we identify over 1,570 essential genetic interactions for autophagy flux, including interactions among paralogous genes, namely ATG2A-ATG2B, GABARAP-MAP1LC3B and GABARAP-GABARAPL2. However, we only observe few genetic interactions within paralogous gene families of more than two members, indicating functional compensation between them. This work establishes 3Cs multiplexing as a platform for genetic interaction screens at scale.