Explore the vast range of titles available.

This study explored the short-term planktonic microbial community structure and resilience in Lake Lanier (GA, USA) while simultaneously evaluating the technical aspects of identifying taxa via 16S rRNA gene amplicon and metagenomic sequence data. 16S rRNA gene amplicons generated from four temporally discrete samples were sequenced with 454 GS-FLX-Ti yielding ∼40,000 rRNA gene sequences from each sample and representing ∼300 observed OTUs. Replicates obtained from the same biological sample clustered together but several biases were observed, linked to either the PCR or sequencing-preparation steps. In comparisons with companion whole-community shotgun metagenome datasets, the estimated number of OTUs at each timepoint was concordant, but 1.5 times and ∼10 times as many phyla and genera, respectively, were identified in the metagenomes. Our analyses showed that the 16S rRNA gene captures broad shifts in community diversity over time, but with limited resolution and lower sensitivity compared to metagenomic data. We also identified OTUs that showed marked shifts in abundance over four close timepoints separated by perturbations and tracked these taxa in the metagenome vs. 16S rRNA amplicon data. A strong summer storm had less of an effect on community composition than did seasonal mixing, which revealed a distinct succession of organisms. This study provides insights into freshwater microbial communities and advances the approaches for assessing community diversity and dynamics in situ.

Bacteria of the SAR11 clade constitute up to one half of all microbial cells in the oxygen-rich surface ocean. SAR11 bacteria are also abundant in oxygen minimum zones (OMZs), where oxygen falls below detection and anaerobic microbes have vital roles in converting bioavailable nitrogen to N 2 gas. Anaerobic metabolism has not yet been observed in SAR11, and it remains unknown how these bacteria contribute to OMZ biogeochemical cycling. Here, genomic analysis of single cells from the world’s largest OMZ revealed previously uncharacterized SAR11 lineages with adaptations for life without oxygen, including genes for respiratory nitrate reductases (Nar). SAR11 nar genes were experimentally verified to encode proteins catalysing the nitrite-producing first step of denitrification and constituted ~40% of OMZ nar transcripts, with transcription peaking in the anoxic zone of maximum nitrate reduction activity. These results link SAR11 to pathways of ocean nitrogen loss, redefining the ecological niche of Earth’s most abundant organismal group. Bacteria of the SAR11 clade constitute up to one half of all marine microbes and are thought to require oxygen for growth; here, a subgroup of SAR11 bacteria are shown to thrive in ocean oxygen minimum zones and to encode abundant respiratory nitrate reductases. An anoxic niche for SAR11 bacteria SAR11 bacteria, the most abundant type of microbe in the world's oceans, are thought to require oxygen for growth, yet they are also abundant in waters where oxygen levels are low. Frank Stewart and colleagues show here that a subgroup of SAR11 bacteria that thrives in ocean oxygen minimum zones have adapted to the microaerobic/anaerobic conditions there, and they encode abundant respiratory nitrate reductases that perform the first step in denitrification. These results redefine the ecological niche of Earth's most abundant organismal group and suggest that they are substantial contributors to nitrogen loss in oxygen minimum zones.

A fundamental question in microbiology is whether there is continuum of genetic diversity among genomes, or clear species boundaries prevail instead. Whole-genome similarity metrics such as Average Nucleotide Identity (ANI) help address this question by facilitating high resolution taxonomic analysis of thousands of genomes from diverse phylogenetic lineages. To scale to available genomes and beyond, we present FastANI, a new method to estimate ANI using alignment-free approximate sequence mapping. FastANI is accurate for both finished and draft genomes, and is up to three orders of magnitude faster compared to alignment-based approaches. We leverage FastANI to compute pairwise ANI values among all prokaryotic genomes available in the NCBI database. Our results reveal clear genetic discontinuity, with 99.8% of the total 8 billion genome pairs analyzed conforming to >95% intra-species and <83% inter-species ANI values. This discontinuity is manifested with or without the most frequently sequenced species, and is robust to historic additions in the genome databases. Average Nucleotide Identity (ANI) is a robust and useful measure to gauge genetic relatedness between two genomes. Here, the authors develop FastANI, a method to compute ANI using alignment-free approximate sequence mapping, and show 95% ANI is an accurate threshold for demarcating prokaryotic species by analyzing about 90,000 prokaryotic genomes.

The SeqCode, formally called the Code of Nomenclature of Prokaryotes Described from Sequence Data, is a new code of nomenclature in which genome sequences are the nomenclatural types for the names of prokaryotic species. While similar to the International Code of Nomenclature of Prokaryotes (ICNP) in structure and rules of priority, it does not require the deposition of type strains in international culture collections. Thus, it allows for the formation of permanent names for uncultured prokaryotes whose nearly complete genome sequences have been obtained directly from environmental DNA as well as other prokaryotes that cannot be deposited in culture collections. Because the diversity of uncultured prokaryotes greatly exceeds that of readily culturable prokaryotes, the SeqCode is the only code suitable for naming the majority of prokaryotic species. The start date of the SeqCode was January 1, 2022, and the online Registry (https://seqco.de/) was created to ensure valid publication of names. The SeqCode recognizes all names validly published under the ICNP before 2022. After that date, names validly published under the SeqCode compete with ICNP names for priority. As a result, species can have only one name, either from the SeqCode or ICNP, enabling effective communication and the creation of unified taxonomies of uncultured and cultured prokaryotes. The SeqCode is administered by the SeqCode Committee, which is comprised of the SeqCode Community and elected administrative components. Anyone with an interest in the systematics of prokaryotes is encouraged to join the SeqCode Community and participate in the development of this resource.

Large-scale surveys of prokaryotic communities (metagenomes), as well as isolate genomes, have revealed that their diversity is predominantly organized in sequence-discrete units that may be equated to species. Specifically, genomes of the same species commonly show genome-aggregate average nucleotide identity (ANI) >95% among themselves and ANI <90% to members of other species, while genomes showing ANI 90%–95% are comparatively rare. However, it remains unclear if such “discontinuities” or gaps in ANI values can be observed within species and thus used to advance and standardize intra-species units. By analyzing 18,123 complete isolate genomes from 330 bacterial species with at least 10 genome representatives each and available long-read metagenomes, we show that another discontinuity exists between 99.2% and 99.8% (midpoint 99.5%) ANI in most of these species. The 99.5% ANI threshold is largely consistent with how sequence types have been defined in previous epidemiological studies but provides clusters with ~20% higher accuracy in terms of evolutionary and gene-content relatedness of the grouped genomes, while strains should be consequently defined at higher ANI values (>99.99% proposed). Collectively, our results should facilitate future micro-diversity studies across clinical or environmental settings because they provide a more natural definition of intra-species units of diversity. Bacterial strains and clonal complexes are two cornerstone concepts for microbiology that remain loosely defined, which confuses communication and research. Here we identify a natural gap in genome sequence comparisons among isolate genomes of all well-sequenced species that has gone unnoticed so far and could be used to more accurately and precisely define these and related concepts compared to current methods. These findings advance the molecular toolbox for accurately delineating and following the important units of diversity within prokaryotic species and thus should greatly facilitate future epidemiological and micro-diversity studies across clinical and environmental settings.

Transcription Activators-Like Effectors (TALEs) belong to a family of virulence proteins from the Xanthomonas genus of bacterial plant pathogens that are translocated into the plant cell. In the nucleus, TALEs act as transcription factors inducing the expression of susceptibility genes. A code for TALE-DNA binding specificity and high-resolution three-dimensional structures of TALE-DNA complexes were recently reported. Accurate prediction of TAL Effector Binding Elements (EBEs) is essential to elucidate the biological functions of the many sequenced TALEs as well as for robust design of artificial TALE DNA-binding domains in biotechnological applications. In this work a program with improved EBE prediction performances was developed using an updated specificity matrix and a position weight correction function to account for the matching pattern observed in a validation set of TALE-DNA interactions. To gain a systems perspective on the large TALE repertoires from X. oryzae strains, this program was used to predict rice gene targets for 99 sequenced family members. Integrating predictions and available expression data in a TALE-gene network revealed multiple candidate transcriptional targets for many TALEs as well as several possible instances of functional convergence among TALEs.

Background Microorganisms in biogas reactors are essential for degradation of organic matter and methane production. However, a comprehensive genome-centric comparison, including relevant metadata for each sample, is still needed to identify the globally distributed biogas community members and serve as a reliable repository. Results Here, 134 publicly available metagenomes derived from different biogas reactors were used to recover 1635 metagenome-assembled genomes (MAGs) representing different biogas bacterial and archaeal species. All genomes were estimated to be > 50% complete and nearly half ≥ 90% complete with ≤ 5% contamination. In most samples, specialized microbial communities were established, while only a few taxa were widespread among the different reactor systems. Metabolic reconstruction of the MAGs enabled the prediction of functional traits related to biomass degradation and methane production from waste biomass. An extensive evaluation of the replication index provided an estimation of the growth dynamics for microbes involved in different steps of the food chain. Conclusions The outcome of this study highlights a high flexibility of the biogas microbiome, allowing it to modify its composition and to adapt to the environmental conditions, including temperatures and a wide range of substrates. Our findings enhance our mechanistic understanding of the AD microbiome and substantially extend the existing repository of genomes. The established database represents a relevant resource for future studies related to this engineered ecosystem.

What a strain is and how many strains make up a natural bacterial population remain elusive concepts despite their apparent importance for assessing the role of intra-population diversity in disease emergence or response to environmental perturbations. To advance these concepts, we sequenced 138 randomly selected Salinibacter ruber isolates from two solar salterns and assessed these genomes against companion short-read metagenomes from the same samples. The distribution of genome-aggregate average nucleotide identity (ANI) values among these isolates revealed a bimodal distribution, with fourfold lower occurrence of values between 99.2% and 99.8% relative to ANI >99.8% or <99.2%, revealing a natural “gap” in the sequence space within species. Accordingly, we used this ANI gap to define genomovars and a higher ANI value of >99.99% and shared gene-content >99.0% to define strains. Using these thresholds and extrapolating from how many metagenomic reads each genomovar uniquely recruited, we estimated that –although our 138 isolates represented about 80% of the Sal. ruber population– the total population in one saltern pond is composed of 5,500 to 11,000 genomovars, the great majority of which appear to be rare in-situ. These data also revealed that the most frequently recovered isolate in lab media was often not the most abundant genomovar in-situ, suggesting that cultivation biases are significant, even in cases that cultivation procedures are thought to be robust. The methodology and ANI thresholds outlined here should represent a useful guide for future microdiversity surveys of additional microbial species.

The composition and prevalence of microorganisms in the middle-to-upper troposphere (8–15 km altitude) and their role in aerosol-cloud-precipitation interactions represent important, unresolved questions for biological and atmospheric science. In particular, airborne microorganisms above the oceans remain essentially uncharacterized, as most work to date is restricted to samples taken near the Earth’s surface. Here we report on the microbiome of low- and high-altitude air masses sampled onboard the National Aeronautics and Space Administration DC-8 platform during the 2010 Genesis and Rapid Intensification Processes campaign in the Caribbean Sea. The samples were collected in cloudy and cloud-free air masses before, during, and after two major tropical hurricanes, Earl and Karl. Quantitative PCR and microscopy revealed that viable bacterial cells represented on average around 20% of the total particles in the 0.25- to 1-μm diameter range and were at least an order of magnitude more abundant than fungal cells, suggesting that bacteria represent an important and underestimated fraction of micrometer-sized atmospheric aerosols. The samples from the two hurricanes were characterized by significantly different bacterial communities, revealing that hurricanes aerosolize a large amount of new cells. Nonetheless, 17 bacterial taxa, including taxa that are known to use C1–C4 carbon compounds present in the atmosphere, were found in all samples, indicating that these organisms possess traits that allow survival in the troposphere. The findings presented here suggest that the microbiome is a dynamic and underappreciated aspect of the upper troposphere with potentially important impacts on the hydrological cycle, clouds, and climate.