RAF-like protein kinases mediate a deeply conserved, rapid auxin response.

The plant-signaling molecule auxin triggers fast and slow cellular responses across land plants and algae. The nuclear auxin pathway mediates gene expression and controls growth and development in land plants, but this pathway is absent from algal sister groups. Several components of rapid responses have been identified in Arabidopsis, but it is unknown if these are part of a conserved mechanism. We recently identified a fast, proteome-wide phosphorylation response to auxin. Here, we show that this response occurs across 5 land plant and algal species and converges on a core group of shared targets. We found conserved rapid physiological responses to auxin in the same species and identified rapidly accelerated fibrosarcoma (RAF)-like protein kinases as central mediators of auxin-triggered phosphorylation across species. Genetic analysis connects this kinase to both auxin-triggered protein phosphorylation and rapid cellular response, thus identifying an ancient mechanism for fast auxin responses in the green lineage.

Comparative Genomics and Physiology of Akkermansia muciniphila Isolates from Human Intestine Reveal Specialized Mucosal Adaptation.

Akkermansia muciniphila is a champion of mucin degradation in the human gastrointestinal tract. Here, we report the isolation of six novel strains from healthy human donors and their genomic, proteomic and physiological characterization in comparison to the type-strains A. muciniphila MucT and A. glycaniphila PytT. Complete genome sequencing revealed that, despite their large genomic similarity (>97.6%), the novel isolates clustered into two distinct subspecies of A. muciniphila: Amuc1, which includes the type-strain MucT, and AmucU, a cluster of unassigned strains that have not yet been well characterized. CRISPR analysis showed all strains to be unique and confirmed that single healthy subjects can carry more than one A. muciniphila strain. Mucin degradation pathways were strongly conserved amongst all isolates, illustrating the exemplary niche adaptation of A. muciniphila to the mucin interface. This was confirmed by analysis of the predicted glycoside hydrolase profiles and supported by comparing the proteomes of A. muciniphila strain H2, belonging to the AmucU cluster, to MucT and A. glycaniphila PytT (including 610 and 727 proteins, respectively). While some intrinsic resistance was observed among the A. muciniphila straind, none of these seem to pose strain-specific risks in terms of their antibiotic resistance patterns nor a significant risk for the horizontal transfer of antibiotic resistance determinants, opening the way to apply the type-strain MucT or these new A. muciniphila strains as next generation beneficial microbes.

SALARECON connects the Atlantic salmon genome to growth and feed efficiency.

Atlantic salmon (Salmo salar) is the most valuable farmed fish globally and there is much interest in optimizing its genetics and rearing conditions for growth and feed efficiency. Marine feed ingredients must be replaced to meet global demand, with challenges for fish health and sustainability. Metabolic models can address this by connecting genomes to metabolism, which converts nutrients in the feed to energy and biomass, but such models are currently not available for major aquaculture species such as salmon. We present SALARECON, a model focusing on energy, amino acid, and nucleotide metabolism that links the Atlantic salmon genome to metabolic fluxes and growth. It performs well in standardized tests and captures expected metabolic (in)capabilities. We show that it can explain observed hypoxic growth in terms of metabolic fluxes and apply it to aquaculture by simulating growth with commercial feed ingredients. Predicted limiting amino acids and feed efficiencies agree with data, and the model suggests that marine feed efficiency can be achieved by supplementing a few amino acids to plant- and insect-based feeds. SALARECON is a high-quality model that makes it possible to simulate Atlantic salmon metabolism and growth. It can be used to explain Atlantic salmon physiology and address key challenges in aquaculture such as development of sustainable feeds.

Assembly and Comparison of Ca. Neoehrlichia mikurensis Genomes.

Ca. Neoehrlichia mikurensis is widely prevalent in I. ricinus across Europe and has been associated with human disease. However, diagnostic modalities are limited, and much is still unknown about its biology. Here, we present the first complete Ca. Neoehrlichia mikurensis genomes directly derived from wildlife reservoir host tissues, using both long- and short-read sequencing technologies. This pragmatic approach provides an alternative to obtaining sufficient material from clinical cases, a difficult task for emerging infectious diseases, and to expensive and challenging bacterial isolation and culture methods. Both genomes exhibit a larger chromosome than the currently available Ca. Neoehrlichia mikurensis genomes and expand the ability to find new targets for the development of supportive laboratory diagnostics in the future. Moreover, this method could be utilized for other tick-borne pathogens that are difficult to culture.

FAIR data station for lightweight metadata management and validation of omics studies.

BACKGROUND: The life sciences are one of the biggest suppliers of scientific data. Reusing and connecting these data can uncover hidden insights and lead to new concepts. Efficient reuse of these datasets is strongly promoted when they are interlinked with a sufficient amount of machine-actionable metadata. While the FAIR (Findable, Accessible, Interoperable, Reusable) guiding principles have been accepted by all stakeholders, in practice, there are only a limited number of easy-to-adopt implementations available that fulfill the needs of data producers. FINDINGS: We developed the FAIR Data Station, a lightweight application written in Java, that aims to support researchers in managing research metadata according to the FAIR principles. It implements the ISA metadata framework and uses minimal information metadata standards to capture experiment metadata. The FAIR Data Station consists of 3 modules. Based on the minimal information model(s) selected by the user, the "form generation module" creates a metadata template Excel workbook with a header row of machine-actionable attribute names. The Excel workbook is subsequently used by the data producer(s) as a familiar environment for sample metadata registration. At any point during this process, the format of the recorded values can be checked using the "validation module." Finally, the "resource module" can be used to convert the set of metadata recorded in the Excel workbook in RDF format, enabling (cross-project) (meta)data searches and, for publishing of sequence data, in an European Nucleotide Archive-compatible XML metadata file. CONCLUSIONS: Turning FAIR into reality requires the availability of easy-to-adopt data FAIRification workflows that are also of direct use for data producers. As such, the FAIR Data Station provides, in addition to the means to correctly FAIRify (omics) data, the means to build searchable metadata databases of similar projects and can assist in ENA metadata submission of sequence data. The FAIR Data Station is available at https://fairbydesign.nl.

Systems Biology in ELIXIR: modelling in the spotlight.

In this white paper, we describe the founding of a new ELIXIR Community - the Systems Biology Community - and its proposed future contributions to both ELIXIR and the broader community of systems biologists in Europe and worldwide. The Community believes that the infrastructure aspects of systems biology - databases, (modelling) tools and standards development, as well as training and access to cloud infrastructure - are not only appropriate components of the ELIXIR infrastructure, but will prove key components of ELIXIR's future support of advanced biological applications and personalised medicine. By way of a series of meetings, the Community identified seven key areas for its future activities, reflecting both future needs and previous and current activities within ELIXIR Platforms and Communities. These are: overcoming barriers to the wider uptake of systems biology; linking new and existing data to systems biology models; interoperability of systems biology resources; further development and embedding of systems medicine; provisioning of modelling as a service; building and coordinating capacity building and training resources; and supporting industrial embedding of systems biology. A set of objectives for the Community has been identified under four main headline areas: Standardisation and Interoperability, Technology, Capacity Building and Training, and Industrial Embedding. These are grouped into short-term (3-year), mid-term (6-year) and long-term (10-year) objectives.

Machine learning approaches to predict the Plant-associated phenotype of Xanthomonas strains.

BACKGROUND: The genus Xanthomonas has long been considered to consist predominantly of plant pathogens, but over the last decade there has been an increasing number of reports on non-pathogenic and endophytic members. As Xanthomonas species are prevalent pathogens on a wide variety of important crops around the world, there is a need to distinguish between these plant-associated phenotypes. To date a large number of Xanthomonas genomes have been sequenced, which enables the application of machine learning (ML) approaches on the genome content to predict this phenotype. Until now such approaches to the pathogenomics of Xanthomonas strains have been hampered by the fragmentation of information regarding pathogenicity of individual strains over many studies. Unification of this information into a single resource was therefore considered to be an essential step. RESULTS: Mining of 39 papers considering both plant-associated phenotypes, allowed for a phenotypic classification of 578 Xanthomonas strains. For 65 plant-pathogenic and 53 non-pathogenic strains the corresponding genomes were available and de novo annotated for the presence of Pfam protein domains used as features to train and compare three ML classification algorithms; CART, Lasso and Random Forest. CONCLUSION: The literature resource in combination with recursive feature extraction used in the ML classification algorithms provided further insights into the virulence enabling factors, but also highlighted domains linked to traits not present in pathogenic strains.

Genomic convergence between Akkermansia muciniphila in different mammalian hosts.

BACKGROUND: Akkermansia muciniphila is a member of the human gut microbiota where it resides in the mucus layer and uses mucin as the sole carbon, nitrogen and energy source. A. muciniphila is the only representative of the Verrucomicrobia phylum in the human gut. However, A. muciniphila 16S rRNA gene sequences have also been found in the intestines of many vertebrates. RESULTS: We detected A. muciniphila-like bacteria in the intestines of animals belonging to 15 out of 16 mammalian orders. In addition, other species belonging to the Verrucomicrobia phylum were detected in fecal samples. We isolated 10 new A. muciniphila strains from the feces of chimpanzee, siamang, mouse, pig, reindeer, horse and elephant. The physiology and genome of these strains were highly similar in comparison to the type strain A. muciniphila MucT. Overall, the genomes of the new strains showed high average nucleotide identity (93.9 to 99.7%). In these genomes, we detected considerable conservation of at least 75 of the 78 mucin degradation genes that were previously detected in the genome of the type strain MucT. CONCLUSIONS: The low genomic divergence observed in the new strains may indicate that A. muciniphila favors mucosal colonization independent of the differences in hosts. In addition, the conserved mucus degradation capability points towards a similar beneficial role of the new strains in regulating host metabolic health.

Galactocerebroside biosynthesis pathways of Mycoplasma species: an antigen triggering Guillain-Barré-Stohl syndrome.

Infection by Mycoplasma pneumoniae has been identified as a preceding factor of Guillain-Barré-Stohl syndrome. The Guillain-Barré-Stohl syndrome is triggered by an immune reaction against the major glycolipids and it has been postulated that M. pneumoniae infection triggers this syndrome due to bacterial production of galactocerebroside. Here, we present an extensive comparison of 224 genome sequences from 104 Mycoplasma species to characterize the genetic determinants of galactocerebroside biosynthesis. Hidden Markov models were used to analyse glycosil transferases, leading to identification of a functional protein domain, termed M2000535 that appears in about a third of the studied genomes. This domain appears to be associated with a potential UDP-glucose epimerase, which converts UDP-glucose into UDP-galactose, a main substrate for the biosynthesis of galactocerebroside. These findings clarify the pathogenic mechanisms underlining the triggering of Guillain-Barré-Stohl syndrome by M. pneumoniae infections.

A chromosome-level assembly of the black tiger shrimp (Penaeus monodon) genome facilitates the identification of growth-associated genes.

To salvage marine ecosystems from fishery overexploitation, sustainable and efficient aquaculture must be emphasized. The knowledge obtained from available genome sequence of marine organisms has accelerated marine aquaculture in many cases. The black tiger shrimp (Penaeus monodon) is one of the most prominent cultured penaeid shrimps (Crustacean) with an average annual global production of half a million tons in the last decade. However, its currently available genome assemblies lack the contiguity and completeness required for accurate genome annotation due to the highly repetitive nature of the genome and technical difficulty in extracting high-quality, high-molecular weight DNA. Here, we report the first chromosome-level whole-genome assembly of P. monodon. The combination of long-read Pacific Biosciences (PacBio) and long-range Chicago and Hi-C technologies enabled a successful assembly of this first high-quality genome sequence. The final assembly covered 2.39 Gb (92.3% of the estimated genome size) and contained 44 pseudomolecules, corresponding to the haploid chromosome number. Repetitive elements occupied a substantial portion of the assembly (62.5%), the highest of the figures reported among crustacean species. The availability of this high-quality genome assembly enabled the identification of genes associated with rapid growth in the black tiger shrimp through the comparison of hepatopancreas transcriptome of slow-growing and fast-growing shrimps. The results highlighted several growth-associated genes. Our high-quality genome assembly provides an invaluable resource for genetic improvement and breeding penaeid shrimp in aquaculture. The availability of P. monodon genome enables analyses of ecological impact, environment adaptation and evolution, as well as the role of the genome to protect the ecological resources by promoting sustainable shrimp farming.

Experimental infrastructure requirements for quantitative research on microbial communities.

Natural microbial communities are composed of a large diversity of interacting microorganisms, each with a specific role in the functional properties of the ecosystem. The objectives in microbial ecology research are related to identifying, understanding and exploring the role of these different microorganisms. Because of the rapidly increasing power of DNA sequencing and the rapid increase of genomic data, main attention of microbial ecology research shifted from cultivation-oriented studies towards metagenomic studies. Despite these efforts, the direct link between the molecular properties and the measurable changes in the functional performance of the ecosystem is often poorly documented. A quantitative understanding of functional properties in relation to the molecular changes requires effective integration, standardization, and parallelization of experiments. High-resolution functional characterization is a prerequisite for interpretation of changes in metagenomic properties, and will improve our understanding of microbial communities and facilitate their exploration for health and circular economy related objectives.

A protocol for adding knowledge to Wikidata: aligning resources on human coronaviruses.

BACKGROUND: Pandemics, even more than other medical problems, require swift integration of knowledge. When caused by a new virus, understanding the underlying biology may help finding solutions. In a setting where there are a large number of loosely related projects and initiatives, we need common ground, also known as a "commons." Wikidata, a public knowledge graph aligned with Wikipedia, is such a commons and uses unique identifiers to link knowledge in other knowledge bases. However, Wikidata may not always have the right schema for the urgent questions. In this paper, we address this problem by showing how a data schema required for the integration can be modeled with entity schemas represented by Shape Expressions. RESULTS: As a telling example, we describe the process of aligning resources on the genomes and proteomes of the SARS-CoV-2 virus and related viruses as well as how Shape Expressions can be defined for Wikidata to model the knowledge, helping others studying the SARS-CoV-2 pandemic. How this model can be used to make data between various resources interoperable is demonstrated by integrating data from NCBI (National Center for Biotechnology Information) Taxonomy, NCBI Genes, UniProt, and WikiPathways. Based on that model, a set of automated applications or bots were written for regular updates of these sources in Wikidata and added to a platform for automatically running these updates. CONCLUSIONS: Although this workflow is developed and applied in the context of the COVID-19 pandemic, to demonstrate its broader applicability it was also applied to other human coronaviruses (MERS, SARS, human coronavirus NL63, human coronavirus 229E, human coronavirus HKU1, human coronavirus OC4).

A metabolic and physiological design study of Pseudomonas putida KT2440 capable of anaerobic respiration.

BACKGROUND: Pseudomonas putida KT2440 is a metabolically versatile, HV1-certified, genetically accessible, and thus interesting microbial chassis for biotechnological applications. However, its obligate aerobic nature hampers production of oxygen sensitive products and drives up costs in large scale fermentation. The inability to perform anaerobic fermentation has been attributed to insufficient ATP production and an inability to produce pyrimidines under these conditions. Addressing these bottlenecks enabled growth under micro-oxic conditions but does not lead to growth or survival under anoxic conditions. RESULTS: Here, a data-driven approach was used to develop a rational design for a P. putida KT2440 derivative strain capable of anaerobic respiration. To come to the design, data derived from a genome comparison of 1628 Pseudomonas strains was combined with genome-scale metabolic modelling simulations and a transcriptome dataset of 47 samples representing 14 environmental conditions from the facultative anaerobe Pseudomonas aeruginosa. CONCLUSIONS: The results indicate that the implementation of anaerobic respiration in P. putida KT2440 would require at least 49 additional genes of known function, at least 8 genes encoding proteins of unknown function, and 3 externally added vitamins.

Publisher Correction: MEMOTE for standardized genome-scale metabolic model testing.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Organohalide-respiring Desulfoluna species isolated from marine environments.

The genus Desulfoluna comprises two anaerobic sulfate-reducing strains, D. spongiiphila AA1T and D. butyratoxydans MSL71T, of which only the former was shown to perform organohalide respiration (OHR). Here we isolated a third strain, designated D. spongiiphila strain DBB, from marine intertidal sediment using 1,4-dibromobenzene and sulfate as the electron acceptors and lactate as the electron donor. Each strain harbors three reductive dehalogenase gene clusters (rdhABC) and corrinoid biosynthesis genes in their genomes, and dehalogenated brominated but not chlorinated organohalogens. The Desulfoluna strains maintained OHR in the presence of 20 mM sulfate or 20 mM sulfide, which often negatively affect other organohalide-respiring bacteria. Strain DBB sustained OHR with 2% oxygen in the gas phase, in line with its genetic potential for reactive oxygen species detoxification. Reverse transcription-quantitative PCR revealed differential induction of rdhA genes in strain DBB in response to 1,4-dibromobenzene or 2,6-dibromophenol. Proteomic analysis confirmed expression of rdhA1 with 1,4-dibromobenzene, and revealed a partially shared electron transport chain from lactate to 1,4-dibromobenzene and sulfate, which may explain accelerated OHR during concurrent sulfate reduction. Versatility in using electron donors, de novo corrinoid biosynthesis, resistance to sulfate, sulfide and oxygen, and concurrent sulfate reduction and OHR may confer an advantage to marine Desulfoluna strains.

Metabolic shift induced by synthetic co-cultivation promotes high yield of chain elongated acids from syngas.

Bio-catalytic processes for sustainable production of chemicals and fuels receive increased attention within the concept of circular economy. Strategies to improve these production processes include genetic engineering of bio-catalysts or process technological optimization. Alternatively, synthetic microbial co-cultures can be used to enhance production of chemicals of interest. It remains often unclear however how microbe to microbe interactions affect the overall production process and how this can be further exploited for application. In the present study we explored the microbial interaction in a synthetic co-culture of Clostridium autoethanogenum and Clostridium kluyveri, producing chain elongated products from carbon monoxide. Monocultures of C. autoethanogenum converted CO to acetate and traces of ethanol, while during co-cultivation with C. kluyveri, it shifted its metabolism significantly towards solventogenesis. In C. autoethanogenum, expression of the genes involved in the central carbon- and energy-metabolism remained unchanged during co-cultivation compared to monoculture condition. Therefore the shift in the metabolic flux of C. autoethanogenum appears to be regulated by thermodynamics, and results from the continuous removal of ethanol by C. kluyveri. This trait could be further exploited, driving the metabolism of C. autoethanogenum to solely ethanol formation during co-cultivation, resulting in a high yield of chain elongated products from CO-derived electrons. This research highlights the important role of thermodynamic interactions in (synthetic) mixed microbial communities and shows that this can be exploited to promote desired conversions.

The Empusa code generator and its application to GBOL, an extendable ontology for genome annotation.

The RDF data model facilitates integration of diverse data available in structured and semi-structured formats. To obtain a coherent RDF graph the chosen ontology must be consistently applied. However, addition of new diverse data causes the ontology to evolve, which could lead to accumulation of unintended erroneous composites. Thus, there is a need for a gate keeping system that compares the intended content described in the ontology with the actual content of the resource. The Empusa code generator facilitates creation of composite RDF resources from disparate sources. Empusa can convert a schema into an associated application programming interface (API), that can be used to perform data consistency checks and generates Markdown documentation to make persistent URLs resolvable. Using Empusa consistency is ensured within and between the ontology and the content of the resource. As an illustration of the potential of Empusa, we present the Genome Biology Ontology Language (GBOL). GBOL uses and extends current ontologies to provide a formal representation of genomic entities, along with their properties, relations and provenance.

Diversity of tryptophan halogenases in sponges of the genus Aplysina.

Marine sponges are a prolific source of novel enzymes with promising biotechnological potential. Especially halogenases, which are key enzymes in the biosynthesis of brominated and chlorinated secondary metabolites, possess interesting properties towards the production of pharmaceuticals that are often halogenated. In this study we used a polymerase chain reaction (PCR)-based screening to simultaneously examine and compare the richness and diversity of putative tryptophan halogenase protein sequences and bacterial community structures of six Aplysina species from the Mediterranean and Caribbean seas. At the phylum level, bacterial community composition was similar amongst all investigated species and predominated by Actinobacteria, Chloroflexi, Cyanobacteria, Gemmatimonadetes, and Proteobacteria. We detected four phylogenetically diverse clades of putative tryptophan halogenase protein sequences, which were only distantly related to previously reported halogenases. The Mediterranean species Aplysina aerophoba harbored unique halogenase sequences, of which the most predominant was related to a sponge-associated Psychrobacter-derived sequence. In contrast, the Caribbean species shared numerous novel halogenase sequence variants and exhibited a highly similar bacterial community composition at the operational taxonomic unit (OTU) level. Correlations of relative abundances of halogenases with those of bacterial taxa suggest that prominent sponge symbiotic bacteria, including Chloroflexi and Actinobacteria, are putative producers of the detected enzymes and may thus contribute to the chemical defense of their host.