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.

Genomic heterogeneity of bacterial species is observed and studied in experimental evolution experiments and clinical diagnostics, and occurs as micro-diversity of natural habitats. The challenge for genome research is to accurately capture this heterogeneity with the currently used short sequencing reads. Recent advances in NGS technologies improved the speed and coverage and thus allowed for deep sequencing of bacterial populations. This facilitates the quantitative assessment of genomic heterogeneity, including low frequency alleles or haplotypes. However, false positive variant predictions due to sequencing errors and mapping artifacts of short reads need to be prevented. We therefore created VarCap, a workflow for the reliable prediction of different types of variants even at low frequencies. In order to predict SNPs, InDels and structural variations, we evaluated the sensitivity and accuracy of different software tools using synthetic read data. The results suggested that the best sensitivity could be reached by a union of different tools, however at the price of increased false positives. We identified possible reasons for false predictions and used this knowledge to improve the accuracy by post-filtering the predicted variants according to properties such as frequency, coverage, genomic environment/localization and co-localization with other variants. We observed that best precision was achieved by using an intersection of at least two tools per variant. This resulted in the reliable prediction of variants above a minimum relative abundance of 2%. VarCap is designed for being routinely used within experimental evolution experiments or for clinical diagnostics. The detected variants are reported as frequencies within a VCF file and as a graphical overview of the distribution of the different variant/allele/haplotype frequencies. The source code of VarCap is available at https://github.com/ma2o/VarCap. In order to provide this workflow to a broad community, we implemeted VarCap on a Galaxy webserver, which is accessible at http://galaxy.csb.univie.ac.at.

Background

Recent studies posit a reciprocal dependency between the microbiomes associated with humans and indoor environments. However, none of these metagenome surveys has considered the viability of constituent microorganisms when inferring impact on human health.

Results

Reported here are the results of a viability-linked metagenomics assay, which (1) unveil a remarkably complex community profile for bacteria, fungi, and viruses and (2) bolster the detection of underrepresented taxa by eliminating biases resulting from extraneous DNA. This approach enabled, for the first time ever, the elucidation of viral genomes from a cleanroom environment. Upon comparing the viable biomes and distribution of phylotypes within a cleanroom and adjoining (uncontrolled) gowning enclosure, the rigorous cleaning and stringent control countermeasures of the former were observed to select for a greater presence of anaerobes and spore-forming microflora. Sequence abundance and correlation analyses suggest that the viable indoor microbiome is influenced by both the human microbiome and the surrounding ecosystem(s).

Conclusions

The findings of this investigation constitute the literature's first ever account of the indoor metagenome derived from DNA originating solely from the potential viable microbial population. Results presented in this study should prove valuable to the conceptualization and experimental design of future studies on indoor microbiomes aimed at inferring impact on human health.

The two-component system (TCS) helps bacteria sense and respond to environmental stimuli through histidine kinases and response regulators. TCSs are the largest family of multistep signal transduction processes, and they are involved in many important cellular processes such as antibiotic resistance, pathogenicity, quorum sensing, osmotic stress, and biofilms. Here, we perform the first comprehensive study to highlight the role of TCSs as potential drug targets against ESKAPEE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp., and Escherichia coli) pathogens through annotation, mapping, pangenomic status, gene orientation, and sequence variation analysis. The distribution of the TCSs is group specific with regard to Gram-positive and Gram-negative bacteria, except for KdpDE. The TCSs among ESKAPEE pathogens form closed pangenomes, except for Pseudomonas aeruginosa Furthermore, their conserved nature due to closed pangenomes might make them good drug targets. Fitness score analysis suggests that any mutation in some TCSs such as BaeSR, ArcBA, EvgSA, and AtoSC, etc., might be lethal to the cell. Taken together, the results of this pangenomic assessment of TCSs reveal a range of strategies deployed by the ESKAPEE pathogens to manifest pathogenicity and antibiotic resistance. This study further suggests that the conserved features of TCSs might make them an attractive group of potential targets with which to address antibiotic resistance.IMPORTANCE The ESKAPEE pathogens are the leading cause of health care-associated infections worldwide. Two-component systems (TCSs) can be used as effective targets against pathogenic bacteria since they are ubiquitous and manage various vital functions such as antibiotic resistance, virulence, biofilms, quorum sensing, and pH balance, among others. This study provides a comprehensive overview of the pangenomic status of the TCSs among ESKAPEE pathogens. The annotation and pangenomic analysis of TCSs show that they are significantly distributed and conserved among the pathogens, as most of them form closed pangenomes. Furthermore, our analysis also reveals that the removal of the TCSs significantly affects the fitness of the cell. Hence, they may be used as promising drug targets against bacteria.

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.

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.

Sulfur-cycling microorganisms impact organic matter decomposition in wetlands and consequently greenhouse gas emissions from these globally relevant environments. However, their identities and physiological properties are largely unknown. By applying a functional metagenomics approach to an acidic peatland, we recovered draft genomes of seven novel Acidobacteria species with the potential for dissimilatory sulfite (dsrAB, dsrC, dsrD, dsrN, dsrT, dsrMKJOP) or sulfate respiration (sat, aprBA, qmoABC plus dsr genes). Surprisingly, the genomes also encoded DsrL, which so far was only found in sulfur-oxidizing microorganisms. Metatranscriptome analysis demonstrated expression of acidobacterial sulfur-metabolism genes in native peat soil and their upregulation in diverse anoxic microcosms. This indicated an active sulfate respiration pathway, which, however, might also operate in reverse for dissimilatory sulfur oxidation or disproportionation as proposed for the sulfur-oxidizing Desulfurivibrio alkaliphilus. Acidobacteria that only harbored genes for sulfite reduction additionally encoded enzymes that liberate sulfite from organosulfonates, which suggested organic sulfur compounds as complementary energy sources. Further metabolic potentials included polysaccharide hydrolysis and sugar utilization, aerobic respiration, several fermentative capabilities, and hydrogen oxidation. Our findings extend both, the known physiological and genetic properties of Acidobacteria and the known taxonomic diversity of microorganisms with a DsrAB-based sulfur metabolism, and highlight new fundamental niches for facultative anaerobic Acidobacteria in wetlands based on exploitation of inorganic and organic sulfur molecules for energy conservation.

CRISPR-Cas systems defend prokaryotic cells from invasive DNA of viruses, plasmids and other mobile genetic elements. Here, we show using metagenomics, metatranscriptomics and single-cell genomics that CRISPR systems of widespread, uncultivated archaea can also target chromosomal DNA of archaeal episymbionts of the DPANN superphylum. Using meta-omics datasets from Crystal Geyser and Horonobe Underground Research Laboratory, we find that CRISPR spacers of the hosts Candidatus Altiarchaeum crystalense and Ca. A. horonobense, respectively, match putative essential genes in their episymbionts' genomes of the genus Ca. Huberiarchaeum and that some of these spacers are expressed in situ. Metabolic interaction modelling also reveals complementation between host-episymbiont systems, on the basis of which we propose that episymbionts are either parasitic or mutualistic depending on the genotype of the host. By expanding our analysis to 7,012 archaeal genomes, we suggest that CRISPR-Cas targeting of genomes associated with symbiotic archaea evolved independently in various archaeal lineages.

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.