Questioning the fetal microbiome illustrates pitfalls of low-biomass microbial studies.

Whether the human fetus and the prenatal intrauterine environment (amniotic fluid and placenta) are stably colonized by microbial communities in a healthy pregnancy remains a subject of debate. Here we evaluate recent studies that characterized microbial populations in human fetuses from the perspectives of reproductive biology, microbial ecology, bioinformatics, immunology, clinical microbiology and gnotobiology, and assess possible mechanisms by which the fetus might interact with microorganisms. Our analysis indicates that the detected microbial signals are likely the result of contamination during the clinical procedures to obtain fetal samples or during DNA extraction and DNA sequencing. Furthermore, the existence of live and replicating microbial populations in healthy fetal tissues is not compatible with fundamental concepts of immunology, clinical microbiology and the derivation of germ-free mammals. These conclusions are important to our understanding of human immune development and illustrate common pitfalls in the microbial analyses of many other low-biomass environments. The pursuit of a fetal microbiome serves as a cautionary example of the challenges of sequence-based microbiome studies when biomass is low or absent, and emphasizes the need for a trans-disciplinary approach that goes beyond contamination controls by also incorporating biological, ecological and mechanistic concepts.

PyCoMo: a python package for community metabolic model creation and analysis.

SUMMARY: PyCoMo is a python package for quick and easy generation of genome-scale compartmentalized community metabolic models that are compliant with current openCOBRA file formats. The resulting models can be used to predict (i) the maximum growth rate at a given abundance profile, (ii) the feasible community compositions at a given growth rate, and (iii) all exchange metabolites and cross-feeding interactions in a community metabolic model independent of the abundance profile; we demonstrate PyCoMo's capability by analysing methane production in a previously published simplified biogas community metabolic model. AVAILABILITY AND IMPLEMENTATION: PyCoMo is freely available under an MIT licence at http://github.com/univieCUBE/PyCoMo, the Python Package Index, and Zenodo.

eggNOG 6.0: enabling comparative genomics across 12 535 organisms.

The eggNOG (evolutionary gene genealogy Non-supervised Orthologous Groups) database is a bioinformatics resource providing orthology data and comprehensive functional information for organisms from all domains of life. Here, we present a major update of the database and website (version 6.0), which increases the number of covered organisms to 12 535 reference species, expands functional annotations, and implements new functionality. In total, eggNOG 6.0 provides a hierarchy of over 17M orthologous groups (OGs) computed at 1601 taxonomic levels, spanning 10 756 bacterial, 457 archaeal and 1322 eukaryotic organisms. OGs have been thoroughly annotated using recent knowledge from functional databases, including KEGG, Gene Ontology, UniProtKB, BiGG, CAZy, CARD, PFAM and SMART. eggNOG also offers phylogenetic trees for all OGs, maximising utility and versatility for end users while allowing researchers to investigate the evolutionary history of speciation and duplication events as well as the phylogenetic distribution of functional terms within each OG. Furthermore, the eggNOG 6.0 website contains new functionality to mine orthology and functional data with ease, including the possibility of generating phylogenetic profiles for multiple OGs across species or identifying single-copy OGs at custom taxonomic levels. eggNOG 6.0 is available at http://eggnog6.embl.de.

Cytoscape stringApp 2.0: Analysis and Visualization of Heterogeneous Biological Networks.

Biological networks are often used to represent complex biological systems, which can contain several types of entities. Analysis and visualization of such networks is supported by the Cytoscape software tool and its many apps. While earlier versions of stringApp focused on providing intraspecies protein-protein interactions from the STRING database, the new stringApp 2.0 greatly improves the support for heterogeneous networks. Here, we highlight new functionality that makes it possible to create networks that contain proteins and interactions from STRING as well as other biological entities and associations from other sources. We exemplify this by complementing a published SARS-CoV-2 interactome with interactions from STRING. We have also extended stringApp with new data and query functionality for protein-protein interactions between eukaryotic parasites and their hosts. We show how this can be used to retrieve and visualize a cross-species network for a malaria parasite, its host, and its vector. Finally, the latest stringApp version has an improved user interface, allows retrieval of both functional associations and physical interactions, and supports group-wise enrichment analysis of different parts of a network to aid biological interpretation. stringApp is freely available at https://apps.cytoscape.org/apps/stringapp.

Molecular causes of an evolutionary shift along the parasitism-mutualism continuum in a bacterial symbiont.

Symbiosis with microbes is a ubiquitous phenomenon with a massive impact on all living organisms, shaping the world around us today. Theoretical and experimental studies show that vertical transmission of symbionts leads to the evolution of mutualistic traits, whereas horizontal transmission facilitates the emergence of parasitic features. However, these studies focused on phenotypic data, and we know little about underlying molecular changes at the genomic level. Here, we combined an experimental evolution approach with infection assays, genome resequencing, and global gene expression analysis to study the effect of transmission mode on an obligate intracellular bacterial symbiont. We show that a dramatic shift in the frequency of genetic variants, coupled with major changes in gene expression, allow the symbiont to alter its position in the parasitism-mutualism continuum depending on the mode of between-host transmission. We found that increased parasitism in horizontally transmitted chlamydiae residing in amoebae was a result of processes occurring at the infectious stage of the symbiont's developmental cycle. Specifically, genes involved in energy production required for extracellular survival and the type III secretion system-the symbiont's primary virulence mechanism-were significantly up-regulated. Our results identify the genomic and transcriptional dynamics sufficient to favor parasitic or mutualistic strategies.

DeepNOG: fast and accurate protein orthologous group assignment.

MOTIVATION: Protein orthologous group databases are powerful tools for evolutionary analysis, functional annotation or metabolic pathway modeling across lineages. Sequences are typically assigned to orthologous groups with alignment-based methods, such as profile hidden Markov models, which have become a computational bottleneck. RESULTS: We present DeepNOG, an extremely fast and accurate, alignment-free orthology assignment method based on deep convolutional networks. We compare DeepNOG against state-of-the-art alignment-based (HMMER, DIAMOND) and alignment-free methods (DeepFam) on two orthology databases (COG, eggNOG 5). DeepNOG can be scaled to large orthology databases like eggNOG, for which it outperforms DeepFam in terms of precision and recall by large margins. While alignment-based methods still provide the most accurate assignments among the investigated methods, computing time of DeepNOG is an order of magnitude lower on CPUs. Optional GPU usage further increases throughput massively. A command-line tool enables rapid adoption by users. AVAILABILITYAND IMPLEMENTATION: Source code and packages are freely available at https://github.com/univieCUBE/deepnog. Install the platform-independent Python program with $pip install deepnog. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Tamock: simulation of habitat-specific benchmark data in metagenomics.

BACKGROUND: Simulated metagenomic reads are widely used to benchmark software and workflows for metagenome interpretation. The results of metagenomic benchmarks depend on the assumptions about their underlying ecosystems. Conclusions from benchmark studies are therefore limited to the ecosystems they mimic. Ideally, simulations are therefore based on genomes, which resemble particular metagenomic communities realistically. RESULTS: We developed Tamock to facilitate the realistic simulation of metagenomic reads according to a metagenomic community, based on real sequence data. Benchmarks samples can be created from all genomes and taxonomic domains present in NCBI RefSeq. Tamock automatically determines taxonomic profiles from shotgun sequence data, selects reference genomes accordingly and uses them to simulate metagenomic reads. We present an example use case for Tamock by assessing assembly and binning method performance for selected microbiomes. CONCLUSIONS: Tamock facilitates automated simulation of habitat-specific benchmark metagenomic data based on real sequence data and is implemented as a user-friendly command-line application, providing extensive additional information along with the simulated benchmark data. Resulting benchmarks enable an assessment of computational methods, workflows, and parameters specifically for a metagenomic habitat or ecosystem of a metagenomic study. AVAILABILITY: Source code, documentation and install instructions are freely available at GitHub ( https://github.com/gerners/tamock ).

Isolate-Based Surveillance of Bordetella pertussis, Austria, 2018-2020.

Pertussis is a vaccine-preventable disease, and its recent resurgence might be attributable to the emergence of strains that differ genetically from the vaccine strain. We describe a novel pertussis isolate-based surveillance system and a core genome multilocus sequence typing scheme to assess Bordetella pertussis genetic variability and investigate the increased incidence of pertussis in Austria. During 2018-2020, we obtained 123 B. pertussis isolates and typed them with the new scheme (2,983 targets and preliminary cluster threshold of <6 alleles). B. pertussis isolates in Austria differed genetically from the vaccine strain, both in their core genomes and in their vaccine antigen genes; 31.7% of the isolates were pertactin-deficient. We detected 8 clusters, 1 of them with pertactin-deficient isolates and possibly part of a local outbreak. National expansion of the isolate-based surveillance system is needed to implement pertussis-control strategies.

Complete nitrification by Nitrospira bacteria.

Nitrification, the oxidation of ammonia via nitrite to nitrate, has always been considered to be a two-step process catalysed by chemolithoautotrophic microorganisms oxidizing either ammonia or nitrite. No known nitrifier carries out both steps, although complete nitrification should be energetically advantageous. This functional separation has puzzled microbiologists for a century. Here we report on the discovery and cultivation of a completely nitrifying bacterium from the genus Nitrospira, a globally distributed group of nitrite oxidizers. The genome of this chemolithoautotrophic organism encodes the pathways both for ammonia and nitrite oxidation, which are concomitantly activated during growth by ammonia oxidation to nitrate. Genes affiliated with the phylogenetically distinct ammonia monooxygenase and hydroxylamine dehydrogenase genes of Nitrospira are present in many environments and were retrieved on Nitrospira-contigs in new metagenomes from engineered systems. These findings fundamentally change our picture of nitrification and point to completely nitrifying Nitrospira as key components of nitrogen-cycling microbial communities.

eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses.

eggNOG is a public database of orthology relationships, gene evolutionary histories and functional annotations. Here, we present version 5.0, featuring a major update of the underlying genome sets, which have been expanded to 4445 representative bacteria and 168 archaea derived from 25 038 genomes, as well as 477 eukaryotic organisms and 2502 viral proteomes that were selected for diversity and filtered by genome quality. In total, 4.4M orthologous groups (OGs) distributed across 379 taxonomic levels were computed together with their associated sequence alignments, phylogenies, HMM models and functional descriptors. Precomputed evolutionary analysis provides fine-grained resolution of duplication/speciation events within each OG. Our benchmarks show that, despite doubling the amount of genomes, the quality of orthology assignments and functional annotations (80% coverage) has persisted without significant changes across this update. Finally, we improved eggNOG online services for fast functional annotation and orthology prediction of custom genomics or metagenomics datasets. All precomputed data are publicly available for downloading or via API queries at http://eggnog.embl.de.

Genome-Wide Mutation Scoring for Machine-Learning-Based Antimicrobial Resistance Prediction.

The prediction of antimicrobial resistance (AMR) based on genomic information can improve patient outcomes. Genetic mechanisms have been shown to explain AMR with accuracies in line with standard microbiology laboratory testing. To translate genetic mechanisms into phenotypic AMR, machine learning has been successfully applied. AMR machine learning models typically use nucleotide k-mer counts to represent genomic sequences. While k-mer representation efficiently captures sequence variation, it also results in high-dimensional and sparse data. With limited training data available, achieving acceptable model performance or model interpretability is challenging. In this study, we explore the utility of feature engineering with several biologically relevant signals. We propose to predict the functional impact of observed mutations with PROVEAN to use the predicted impact as a new feature for each protein in an organism's proteome. The addition of the new features was tested on a total of 19,521 isolates across nine clinically relevant pathogens and 30 different antibiotics. The new features significantly improved the predictive performance of trained AMR models for Pseudomonas aeruginosa, Citrobacter freundii, and Escherichia coli. The balanced accuracy of the respective models of those three pathogens improved by 6.0% on average.

Revealing the Venomous Secrets of the Spider's Web.

Orb-weaving spiders use a highly strong, sticky and elastic web to catch their prey. These web properties alone would be enough for the entrapment of prey; however, these spiders may be hiding venomous secrets in the web, which current research is revealing. Here, we provide strong proteotranscriptomic evidence for the presence of toxin/neurotoxin-like proteins, defensins, and proteolytic enzymes on the web silk from Nephila clavipes spider. The results from quantitative-based transcriptomic and proteomic approaches showed that silk-producing glands produce an extensive repertoire of toxin/neurotoxin-like proteins, similar to those already reported in spider venoms. Meanwhile, the insect toxicity results demonstrated that these toxic components can be lethal and/or paralytic chemical weapons used for prey capture on the web, and the presence of fatty acids in the web may be a responsible mechanism opening the way to the web toxins for accessing the interior of prey's body, as shown here. Comparative phylogenomic-level evolutionary analyses revealed orthologous genes among two spider groups, Araneomorphae and Mygalomorphae, and the findings showed protein sequences similar to toxins found in the taxa Scorpiones and Hymenoptera in addition to Araneae. Overall, these data represent a valuable resource to further investigate other spider web toxin systems and also suggest that N. clavipes web is not a passive mechanical trap for prey capture, but it exerts an active role in prey paralysis/killing using a series of neurotoxins.

Proteome Changes Paralleling the Olfactory Conditioning in the Forager Honey Bee and Provision of a Brain Proteomics Dataset.

The olfactory conditioning of the bee proboscis extension reflex (PER) is extensively used as a paradigm in associative learning of invertebrates but with limited molecular investigations. To investigate which protein changes are linked to olfactory conditioning, a non-sophisticated conditioning model is applied using the PER in the honeybee (Apis mellifera). Foraging honeybees are assigned into three groups based on the reflex behavior and training: conditioned using 2-octanone (PER-conditioned), and sucrose and water controls. Thereafter, the brain synaptosomal proteins are isolated and analyzed by quantitative proteomics using stable isotope labeling (TMT). Additionally, the complex proteome dataset of the bee brain is generated with a total number of 5411 protein groups, including key players in neurotransmitter signaling. The most significant categories affected during olfactory conditioning are associated with "SNARE interactions in vesicular transport" (BET1 and VAMP7), ABC transporters, and fatty acid degradation pathways.

Hybrid de novo transcriptome assembly of poinsettia (Euphorbia pulcherrima Willd. Ex Klotsch) bracts.

BACKGROUND: Poinsettia is a popular and important ornamental crop, mostly during the Christmas season. Its bract coloration ranges from pink/red to creamy/white shades. Despite its ornamental value, there is a lack of knowledge about the genetics and molecular biology of poinsettia, especially on the mechanisms of color formation. We performed an RNA-Seq analysis in order to shed light on the transcriptome of poinsettia bracts. Moreover, we analyzed the transcriptome differences of red- and white-bracted poinsettia varieties during bract development and coloration. For the assembly of a bract transcriptome, two paired-end cDNA libraries from a red and white poinsettia pair were sequenced with the Illumina technology, and one library from a red-bracted variety was used for PacBio sequencing. Both short and long reads were assembled using a hybrid de novo strategy. Samples of red- and white-bracted poinsettias were sequenced and comparatively analyzed in three color developmental stages in order to understand the mechanisms of color formation and accumulation in the species. RESULTS: The final transcriptome contains 288,524 contigs, with 33% showing confident protein annotation against the TAIR10 database. The BUSCO pipeline, which is based on near-universal orthologous gene groups, was applied to assess the transcriptome completeness. From a total of 1440 BUSCO groups searched, 77% were categorized as complete (41% as single-copy and 36% as duplicated), 10% as fragmented and 13% as missing BUSCOs. The gene expression comparison between red and white varieties of poinsettia showed a differential regulation of the flavonoid biosynthesis pathway only at particular stages of bract development. An initial impairment of the flavonoid pathway early in the color accumulation process for the white poinsettia variety was observed, but these differences were no longer present in the subsequent stages of bract development. Nonetheless, GSTF11 and UGT79B10 showed a lower expression in the last stage of bract development for the white variety and, therefore, are potential candidates for further studies on poinsettia coloration. CONCLUSIONS: In summary, this transcriptome analysis provides a valuable foundation for further studies on poinsettia, such as plant breeding and genetics, and highlights crucial information on the molecular mechanism of color formation.

Highly variable mRNA half-life time within marine bacterial taxa and functional genes.

Messenger RNA can provide valuable insights into the variability of metabolic processes of microorganisms. However, due to uncertainties that include the stability of RNA, its application for activity profiling of environmental samples is questionable. We explored different factors affecting the decay rate of transcripts of three marine bacterial isolates using qPCR and determined mRNA half-life time of specific bacterial taxa and of functional genes by metatranscriptomics of a coastal environmental prokaryotic community. The half-life time of transcripts from 11 genes from bacterial isolates ranged from 1 to 46 min. About 80% of the analysed transcripts exhibited half-live times shorter than 10 min. Significant differences were found in the half-life time between mRNA and rRNA. The half-life time of mRNA obtained from a coastal metatranscriptome ranged from 9 to 400 min. The shortest half-life times of the metatranscriptome corresponded to transcripts from the same clusters of orthologous groups (COGs) in all bacterial classes. The prevalence of short mRNA half-life time in genes related to defence mechanisms and motility indicate a tight connection of RNA decay rate to environmental stressors. The short half-life time of RNA and its high variability needs to be considered when assessing metatranscriptomes especially in environmental samples.

Characterization of a thaumarchaeal symbiont that drives incomplete nitrification in the tropical sponge Ianthella basta.

Marine sponges represent one of the few eukaryotic groups that frequently harbour symbiotic members of the Thaumarchaeota, which are important chemoautotrophic ammonia-oxidizers in many environments. However, in most studies, direct demonstration of ammonia-oxidation by these archaea within sponges is lacking, and little is known about sponge-specific adaptations of ammonia-oxidizing archaea (AOA). Here, we characterized the thaumarchaeal symbiont of the marine sponge Ianthella basta using metaproteogenomics, fluorescence in situ hybridization, qPCR and isotope-based functional assays. 'Candidatus Nitrosospongia ianthellae' is only distantly related to cultured AOA. It is an abundant symbiont that is solely responsible for nitrite formation from ammonia in I. basta that surprisingly does not harbour nitrite-oxidizing microbes. Furthermore, this AOA is equipped with an expanded set of extracellular subtilisin-like proteases, a metalloprotease unique among archaea, as well as a putative branched-chain amino acid ABC transporter. This repertoire is strongly indicative of a mixotrophic lifestyle and is (with slight variations) also found in other sponge-associated, but not in free-living AOA. We predict that this feature as well as an expanded and unique set of secreted serpins (protease inhibitors), a unique array of eukaryotic-like proteins, and a DNA-phosporothioation system, represent important adaptations of AOA to life within these ancient filter-feeding animals.

Oxytocin-like signaling in ants influences metabolic gene expression and locomotor activity.

Ants are emerging model systems to study cellular signaling because distinct castes possess different physiologic phenotypes within the same colony. Here we studied the functionality of inotocin signaling, an insect ortholog of mammalian oxytocin (OT), which was recently discovered in ants. In Lasius ants, we determined that specialization within the colony, seasonal factors, and physiologic conditions down-regulated the expression of the OT-like signaling system. Given this natural variation, we interrogated its function using RNAi knockdowns. Next-generation RNA sequencing of OT-like precursor knock-down ants highlighted its role in the regulation of genes involved in metabolism. Knock-down ants exhibited higher walking activity and increased self-grooming in the brood chamber. We propose that OT-like signaling in ants is important for regulating metabolic processes and locomotion.-Liutkeviciute, Z., Gil-Mansilla, E., Eder, T., Casillas-Pérez, B., Di Giglio, M. G., Muratspahic, E., Grebien, F., Rattei, T., Muttenthaler, M., Cremer, S., Gruber, C. W. Oxytocin-like signaling in ants influences metabolic gene expression and locomotor activity.

Genomic insights into the Acidobacteria reveal strategies for their success in terrestrial environments.

Members of the phylum Acidobacteria are abundant and ubiquitous across soils. We performed a large-scale comparative genome analysis spanning subdivisions 1, 3, 4, 6, 8 and 23 (n = 24) with the goal to identify features to help explain their prevalence in soils and understand their ecophysiology. Our analysis revealed that bacteriophage integration events along with transposable and mobile elements influenced the structure and plasticity of these genomes. Low- and high-affinity respiratory oxygen reductases were detected in multiple genomes, suggesting the capacity for growing across different oxygen gradients. Among many genomes, the capacity to use a diverse collection of carbohydrates, as well as inorganic and organic nitrogen sources (such as via extracellular peptidases), was detected - both advantageous traits in environments with fluctuating nutrient environments. We also identified multiple soil acidobacteria with the potential to scavenge atmospheric concentrations of H2 , now encompassing mesophilic soil strains within the subdivision 1 and 3, in addition to a previously identified thermophilic strain in subdivision 4. This large-scale acidobacteria genome analysis reveal traits that provide genomic, physiological and metabolic versatility, presumably allowing flexibility and versatility in the challenging and fluctuating soil environment.

Reef invertebrate viromics: diversity, host specificity and functional capacity.

Recent metagenomic analyses have revealed a high diversity of viruses in the pelagic ocean and uncovered clear habitat-specific viral distribution patterns. Conversely, similar insights into the composition, host specificity and function of viruses associated with marine organisms have been limited by challenges associated with sampling and computational analysis. Here, we performed targeted viromic analysis of six coral reef invertebrate species and their surrounding seawater to deliver taxonomic and functional profiles of viruses associated with reef organisms. Sponges and corals' host species-specific viral assemblages with low sequence identity to known viral genomes. While core viral genes involved in capsid formation, tail structure and infection mechanisms were observed across all reef samples, auxiliary genes including those involved in herbicide resistance and viral pathogenesis pathways such as host immune suppression were differentially enriched in reef hosts. Utilising a novel OTU based assessment, we also show a prevalence of dsDNA viruses belonging to the Mimiviridae, Caudovirales and Phycodnaviridae in reef environments and further highlight the abundance of ssDNA viruses belonging to the Circoviridae, Parvoviridae, Bidnaviridae and Microviridae in reef invertebrates. These insights into coral reef viruses provide an important framework for future research into how viruses contribute to the health and evolution of reef organisms.

Viruses comprise an extensive pool of mobile genetic elements in eukaryote cell cultures and human clinical samples.

Viruses shape a diversity of ecosystems by modulating their microbial, eukaryotic, or plant host metabolism. The complexity of virus-host interaction networks is progressively fathomed by novel metagenomic approaches. By using a novel metagenomic method, we explored the virome in mammalian cell cultures and clinical samples to identify an extensive pool of mobile genetic elements in all of these ecosystems. Despite aseptic treatment, cell cultures harbored extensive and diverse phage populations with a high abundance of as yet unknown and uncharacterized viruses (viral dark matter). Unknown phages also predominated in the oropharynx and urine of healthy individuals and patients infected with cytomegalovirus despite demonstration of active cytomegalovirus replication. The novelty of viral sequences correlated primarily with the individual evaluated, whereas relative abundance of encoded protein functions was associated with the ecologic niches probed. Together, these observations demonstrate the extensive presence of viral dark matter in human and artificial ecosystems.-Thannesberger, J., Hellinger, H.-J., Klymiuk, I., Kastner, M.-T., Rieder, F. J. J., Schneider, M., Fister, S., Lion, T., Kosulin, K., Laengle, J., Bergmann, M., Rattei, T., Steininger, C. Viruses comprise an extensive pool of mobile genetic elements in eukaryote cell cultures and human clinical samples.