The predictive power of phylogeny on growth rates in soil bacterial communities

Improved maximum growth rate prediction from microbial genomes by integrating phylogenetic information

Microbial maximum growth rates vary widely across species and are key parameters for ecosystem modeling. Measuring these rates is challenging, but genomic features like codon usage statistics provide useful signals for predicting growth rates for as-yet uncultivated organisms. Here we present Phydon, a framework for genome-based maximum growth rate prediction that combines codon statistics and phylogenetic information to enhance the precision of maximum growth rate estimates, especially when a close relative with a known growth rate is available. We use Phydon to construct a large and taxonomically broad database of temperature-corrected growth rate estimates for 111,349 microbial species. The results reveal a bimodal distribution of maximum growth rates, resolving distinct groups of fast and slow growers. Our work provides insight into the predictive power of taxonomic information versus mechanistic, gene-based inference.

Comparing field and lab quantitative stable isotope probing for nitrogen assimilation in soil microbes

Soil microbial communities play crucial roles in nutrient cycling and can help retain nitrogen in agricultural soils. Quantitative stable isotope probing (qSIP) is a useful method for investigating taxon-specific microbial growth and utilization of specific nutrients, such as nitrogen (N). Typically, qSIP is performed in a highly controlled lab setting, so the field relevance of lab qSIP studies remains unknown. We conducted and compared tandem lab and field qSIP to quantify the assimilation of 15N by maize-associated soil prokaryotic communities at two agricultural sites. Here, we show that field qSIP with 15N can be used to measure taxon-specific microbial N assimilation. Relative 15N assimilation rates were generally lower in the field, and the magnitude of this difference varied by site. Rates differed by method (lab vs field) for 19% of the top N assimilating genera. The field and lab measures were more comparable when relative assimilation rates were weighted by relative abundance to estimate the proportion of N assimilated by each genus with only ~10% of taxa differing by method. Of those that differed, the taxa consistently higher in the lab were inclined to have opportunistic lifestyle strategies, whereas those higher in the field had niches reliant on plant roots or in-tact soil structure (biofilms, mycelia). This study demonstrates that 15N-qSIP can be successfully performed using field-incubated soils to identify microbial allies in N retention and highlights the strengths and limitations of field and lab qSIP approaches.

IMPORTANCE

Soil microbes are responsible for critical biogeochemical processes in natural and agricultural ecosystems. Despite their importance, the functional traits of most soil organisms remain woefully under-characterized, limiting our ability to understand how microbial populations influence the transformation of elements such as nitrogen (N) in soil. Quantitative stable isotope probing (qSIP) is a powerful tool to measure the traits of individual taxa. This method has rarely been applied in the field or with 15N to measure nitrogen assimilation. In this study, we measured genus-specific microbial nitrogen assimilation in two agricultural soils and compared field and lab 15N qSIP methods. Our results identify taxa important for nitrogen assimilation in agricultural soils, shed light on the field relevance of lab qSIP studies, and provide guidance for the future application of qSIP to measure microbial traits in the field.

Closely Related Brucella Species Widely Differ in their Vegetative and Intracellular Growth

Growth rate is a key prokaryotic trait that allows for estimating fitness and understanding cell metabolism. While it has been well studied in model organisms, there is limited data on slow-growing bacteria. In particular, there is a lack of quantitative studies on Brucella species. This genus includes important microorganisms that are causative agents of brucellosis, one of the most widespread bacterial zoonoses, affecting several species of animals, including humans. Brucella species exhibit approximately 97% genomic similarity. Despite this, Brucella species show different host preferences, zoonotic risks, and pathogenicity. After more than one hundred years of research, numerous aspects of Brucella biology, such as in vivo and in vitro growth, remain poorly characterized. In this work, we analyzed vegetative and intracellular growth of the classical Brucella species (B. abortus, B. melitensis, B. suis, B. ovis, and B. canis). Strikingly, each species displayed distinct growth parameters in culture. Doubling time (DT) ranged from 2.7 hs-1 in B. suis to 18 h-1 for B. ovis. In the context of intracellular infection of J774A.1 phagocytic cells, DT was longer, but it widely varied across species, closely correlating with the growth observed in vitro. Overall, and despite high genome similarity, we also found species-specific growth parameters in the intracellular cell cycle.

Enhanced carbon use efficiency and warming resistance of soil microorganisms under organic amendment

The frequency and intensity of extreme weather events, including rapid temperature fluctuations, are increasing because of climate change. Long-term fertilization practices have been observed to alter microbial physiology and community structure, thereby affecting soil carbon sequestration. However, the effects of warming on the carbon sequestration potential of soil microbes adapted to long-term fertilization remain poorly understood. In this study, we utilized 18O isotope labeling to assess microbial carbon use efficiency (CUE) and employed stable isotope probing (SIP) with 18O-H2O to identify growing taxa in response to temperature changes (5-35 °C). Organic amendment with manure or straw residue significantly increased microbial CUE by 86-181 % compared to unfertilized soils. The microorganisms inhabiting organic amended soils displayed greater resistance of microbial CUE to high temperatures (25-35 °C) compared to those inhabiting soils fertilized only with minerals. Microbial growth patterns determined by the classification of taxa into incorporators or non-incorporators based on 18O incorporation into DNA exhibited limited phylogenetic conservation in response to temperature changes. Microbial clusters were identified by grouping taxa with similar growth patterns across different temperatures. Organic amendments enriched microbial clusters associated with increased CUE, whereas clusters in unfertilized or mineral-only fertilized soils were linked to decreased CUE. Specifically, shifts in the composition of growing bacteria were correlated with enhanced microbial CUE, whereas modifications in the composition of growing fungi were associated with diminished CUE. Notably, the responses of microbial CUE to temperature fluctuations were primarily driven by changes in the bacterial composition. Overall, our findings demonstrate that organic amendments enhance soil microbial CUE and promote the enrichment of specific microbial clusters that are better equipped to cope with temperature changes. This study establishes a theoretical foundation for manipulating soil microbes to enhance carbon sequestration under global climate scenarios.

DeepPL: A deep-learning-based tool for the prediction of bacteriophage lifecycle

Bacteriophages (phages) are viruses that infect bacteria and can be classified into two different lifecycles. Virulent phages (or lytic phages) have a lytic cycle that can lyse the bacteria host after their infection. Temperate phages (or lysogenic phages) can integrate their phage genomes into bacterial chromosomes and replicate with bacterial hosts via the lysogenic cycle. Identifying phage lifecycles is a crucial step in developing suitable applications for phages. Compared to the complicated traditional biological experiments, several tools have been designed for predicting phage lifecycle using different algorithms, such as random forest (RF), linear support-vector classifier (SVC), and convolutional neural network (CNN). In this study, we developed a natural language processing (NLP)-based tool-DeepPL-for predicting phage lifecycles via nucleotide sequences. The test results showed that our DeepPL had an accuracy of 94.65% with a sensitivity of 92.24% and a specificity of 95.91%. Moreover, DeepPL had 100% accuracy in lifecycle prediction on the phages we isolated and biologically verified previously in the lab. Additionally, a mock phage community metagenomic dataset was used to test the potential usage of DeepPL in viral metagenomic research. DeepPL displayed a 100% accuracy for individual phage complete genomes and high accuracies ranging from 71.14% to 100% on phage contigs produced by various next-generation sequencing technologies. Overall, our study indicates that DeepPL has a reliable performance on phage lifecycle prediction using the most fundamental nucleotide sequences and can be applied to future phage and metagenomic research.

The Role of Soil Microbial Consortia in Sustainable Cereal Crop Residue Management

The global escalation in cereal production, essential to meet growing population demands, simultaneously augments the generation of cereal crop residues, estimated annually at approximately 3107 × 106 Mg/year. Among different crop residue management approaches, returning them to the soil can be essential for various ecological benefits, including nutrient recycling and soil carbon sequestration. However, the recalcitrant characteristics of cereal crop residues pose significant challenges in their management, particularly in the decomposition rate. Therefore, in this review, we aim to summarize the influence of different agricultural practices on enhancing soil microbial decomposer communities, thereby effectively managing cereal crop residues. Moreover, this manuscript provides indirect estimates of cereal crop residue production in Northern Europe and Lithuania, and highlights the diverse roles of lignocellulolytic microorganisms in the decomposition process, with a particular focus on enzymatic activities. This review bridges the knowledge gap and indicates future research directions concerning the influence of agricultural practices on cereal crop residue-associated microbial consortia.

Phylogenetic distribution and experimental characterization of corrinoid production and dependence in soil bacterial isolates

Soil microbial communities impact carbon sequestration and release, biogeochemical cycling, and agricultural yields. These global effects rely on metabolic interactions that modulate community composition and function. However, the physicochemical and taxonomic complexity of soil and the scarcity of available isolates for phenotypic testing are significant barriers to studying soil microbial interactions. Corrinoids-the vitamin B12 family of cofactors-are critical for microbial metabolism, yet they are synthesized by only a subset of microbiome members. Here, we evaluated corrinoid production and dependence in soil bacteria as a model to investigate the ecological roles of microorganisms involved in metabolic interactions. We isolated and characterized a taxonomically diverse collection of 161 soil bacteria from a single study site. Most corrinoid-dependent bacteria in the collection prefer B12 over other corrinoids, while all tested producers synthesize B12, indicating metabolic compatibility between producers and dependents in the collection. Furthermore, a subset of producers release B12 at levels sufficient to support dependent isolates in laboratory culture at estimated ratios of up to 1000 dependents per producer. Within our isolate collection, we did not find strong phylogenetic patterns in corrinoid production or dependence. Upon investigating trends in the phylogenetic dispersion of corrinoid metabolism categories across sequenced bacteria from various environments, we found that these traits are conserved in 47 out of 85 genera. Together, these phenotypic and genomic results provide evidence for corrinoid-based metabolic interactions among bacteria and provide a framework for the study of nutrient-sharing ecological interactions in microbial communities.