Building a genome-based understanding of bacterial pH preferences

Biochar of invasive plants alleviated impact of acid rain on soil microbial community structure and functionality better than liming

Acid rain and invasive plants have quintessential adverse impacts on terrestrial ecosystems. As an environmentally safe method for disposal of invasive plants, we tested the effect of biochar produced from these plants in altering soil deterioration under acid rain as compared with lime. Given the impacts of the feedstock type and soil properties on the response of soil to the added biochar, we hypothesized that the microbial community and functions would respond differently to the charred invasive plants under acid rain. A pot experiment was conducted to examine the response of soil microbiomes and functions to the biochar produced from Blackjack (Biden Pilosa), Wedelia (Wedelia trilobata), and Bitter vine (Mikania micrantha Kunth), or quicklime (CaO) at a rate of 1 % (w/w) under acid rain. Like soil pH, the nutrient contents (nitrogen, phosphorus, and potassium), calcium, and cation exchange capacity (CEC) were important as dominant edaphic factors affecting soil microbial community and functionality. In this respect, lime decreased nutrients availability, driven by 11-fold, 44 %, and 2-fold increments in calcium content, pH, and C/N ratio. Meanwhile, biochar improved nutrients availability under acid rain owing to maintaining a neutral pH (∼6.5), increasing calcium (by only 2-fold), and improving CEC, water repellency, and aggregation while decreasing the C/N ratio and aluminum content. Unlike biochar, lime decreased the relative abundance of Nitrosomonadaceae (the dominant ammonia-oxidizing bacteria) while augmenting the relative abundance of some fungal pathogens such as Spizellomycetaceae and Sporormiaceae. Given the highest nitrogen and dissolved organic carbon content than other biochar types, Wedelia-biochar resulted in the greatest relative abundance of Nitrosomonadaceae; thus, the microbial carbon and nitrogen biomasses were maximized. This study outlined the responses of the soil biogeochemical properties and the related microbial community structure and functionality to the biochar produced from invasive plants under acid rain. This study suggests that biochar can replace lime to ameliorate the effects of acid rain on soil physical, chemical and biological properties.

An ecological-evolutionary perspective on the genomic diversity and habitat preferences of the Acidobacteriota

Members of the phylum Acidobacteriota inhabit a wide range of ecosystems including soils. We analyzed the global patterns of distribution and habitat preferences of various Acidobacteriota lineages across major ecosystems (soil, engineered, host-associated, marine, non-marine saline and alkaline, and terrestrial non-soil ecosystem) in 248,559 publicly available metagenomic datasets. Classes Terriglobia, Vicinamibacteria, Blastocatellia, and Thermoanaerobaculia were highly ubiquitous and showed clear preference to soil over non-soil habitats, class Polarisedimenticolia showed comparable ubiquity and preference between soil and non-soil habitats, while classes Aminicenantia and Holophagae showed preferences to non-soil habitats. However, while specific preferences were observed, most Acidobacteriota lineages were habitat generalists rather than specialists, with genomic and/or metagenomic fragments recovered from soil and non-soil habitats at various levels of taxonomic resolution. Comparative analysis of 1930 genomes strongly indicates that phylogenetic affiliation plays a more important role than the habitat from which the genome was recovered in shaping the genomic characteristics and metabolic capacities of the Acidobacteriota. The observed lack of strong habitat specialization and habitat transition driven lineage evolution in the Acidobacteriota suggest ready cross colonization between soil and non-soil habitats. We posit that such capacity is key to the successful establishment of Acidobacteriota as a major component in soil microbiomes post ecosystem disturbance events or during pedogenesis.

Functional regimes define the response of the soil microbiome to environmental change

The metabolic activity of soil microbiomes plays a central role in carbon and nitrogen cycling. Given the changing climate, it is important to understand how the metabolism of natural communities responds to environmental change. However, the ecological, spatial, and chemical complexity of soils makes understanding the mechanisms governing the response of these communities to perturbations challenging. Here, we overcome this complexity by using dynamic measurements of metabolism in microcosms and modeling to reveal regimes where a few key mechanisms govern the response of soils to environmental change. We sample soils along a natural pH gradient, construct >1500 microcosms to perturb the pH, and quantify the dynamics of respiratory nitrate utilization, a key process in the nitrogen cycle. Despite the complexity of the soil microbiome, a minimal mathematical model with two variables, the quantity of active biomass in the community and the availability of a growth-limiting nutrient, quantifies observed nitrate utilization dynamics across soils and pH perturbations. Across environmental perturbations, changes in these two variables give rise to three functional regimes each with qualitatively distinct dynamics of nitrate utilization over time: a regime where acidic perturbations induce cell death that limits metabolic activity, a nutrient-limiting regime where nitrate uptake is performed by dominant taxa that utilize nutrients released from the soil matrix, and a resurgent growth regime in basic conditions, where excess nutrients enable growth of initially rare taxa. The underlying mechanism of each regime is predicted by our interpretable model and tested via amendment experiments, nutrient measurements, and sequencing. Further, our data suggest that the long-term history of environmental variation in the wild influences the transitions between functional regimes. Therefore, quantitative measurements and a mathematical model reveal the existence of qualitative regimes that capture the mechanisms and dynamics of a community responding to environmental change.

Why does increased microbial fermentation in the human colon shift toward butyrate?

The microbial community of the human large intestine mainly ferments dietary fiber to short chain fatty acids (SCFAs), which are efficiently absorbed by the host. The three major SCFAs (acetate, propionate, and butyrate) have different fates within the body and different effects on health. A recent analysis of 10 human volunteer studies established that the proportions of these SCFA in fecal samples significantly shifted towards butyrate as the overall concentration of SCFA increased. Butyrate plays a key role in gut health and is preferentially utilized as an energy source by the colonic epithelium. Here we discuss possible mechanisms that underlie this 'butyrate shift'; these include the selection for butyrate-producing bacteria within the microbiota by certain types of fiber, and the possibility of additional butyrate formation from lactate and acetate by metabolite cross-feeding. However, a crucial factor appears to be the pH in the proximal colon, which decreases as the SCFA concentrations increase. A mildly acidic pH has been shown to have an important impact on microbial competition and on the stoichiometry of butyrate production. Understanding these complex interactions has been greatly aided by the refinement of theoretical models of the colonic microbiota that assume a small number (10) of microbial functional groups (MFGs).

Genomic and environmental controls on Castellaniella biogeography in an anthropogenically disturbed subsurface

Castellaniella species have been isolated from a variety of mixed-waste environments including the nitrate and multiple metal-contaminated subsurface at the Oak Ridge Reservation (ORR). Previous studies examining microbial community composition and nitrate removal at ORR during biostimulation efforts reported increased abundances of members of the Castellaniella genus concurrent with increased denitrification rates. Thus, we asked how genomic and abiotic factors control the Castellaniella biogeography at the site to understand how these factors may influence nitrate transformation in an anthropogenically impacted setting. We report the isolation and characterization of several Castellaniella strains from the ORR subsurface. Five of these isolates match at 100% identity (at the 16S rRNA gene V4 region) to two Castellaniella amplicon sequence variants (ASVs), ASV1 and ASV2, that have persisted in the ORR subsurface for at least 2 decades. However, ASV2 has consistently higher relative abundance in samples taken from the site and was also the dominant blooming denitrifier population during a prior biostimulation effort. We found that the ASV2 representative strain has greater resistance to mixed metal stress than the ASV1 representative strains. We attribute this resistance, in part, to the large number of unique heavy metal resistance genes identified on a genomic island in the ASV2 representative genome. Additionally, we suggest that the relatively lower fitness of ASV1 may be connected to the loss of the nitrous oxide reductase (nos) operon (and associated nitrous oxide reductase activity) due to the insertion at this genomic locus of a mobile genetic element carrying copper resistance genes. This study demonstrates the value of integrating genomic, environmental, and phenotypic data to characterize the biogeography of key microorganisms in contaminated sites.

The native distribution of a common legume shrub is limited by the range of its nitrogen-fixing mutualist

Plant-microbe mutualisms, such as the legume-rhizobium symbiosis, are influenced by the geographical distributions of both partners. However, limitations on the native range of legumes, resulting from the absence of a compatible mutualist, have rarely been explored. We used a combination of a large-scale field survey and controlled experiments to determine the realized niche of Calicotome villosa, an abundant and widespread legume shrub. Soil type was a major factor affecting the distribution and abundance of C. villosa. In addition, we found a large region within its range in which neither C. villosa nor Bradyrhizobium, the bacterial genus that associates with it, were present. Seedlings grown in soil from this region failed to nodulate and were deficient in nitrogen. Inoculation of this soil with Bradyrhizobium isolated from root nodules of C. villosa resulted in the formation of nodules and higher growth rate, leaf N and shoot biomass compared with un-inoculated plants. We present evidence for the exclusion of a legume from parts of its native range by the absence of a compatible mutualist. This result highlights the importance of the co-distribution of both the host plant and its mutualist when attempting to understand present and future geographical distributions of legumes.

MotGen: a closed-loop bacterial motility control framework using generative adversarial networks

MOTIVATION

Many organisms' survival and behavior hinge on their responses to environmental signals. While research on bacteria-directed therapeutic agents has increased, systematic exploration of real-time modulation of bacterial motility remains limited. Current studies often focus on permanent motility changes through genetic alterations, restricting the ability to modulate bacterial motility dynamically on a large scale. To address this gap, we propose a novel real-time control framework for systematically modulating bacterial motility dynamics.

RESULTS

We introduce MotGen, a deep learning approach leveraging Generative Adversarial Networks to analyze swimming performance statistics of motile bacteria based on live cell imaging data. By tracking objects and optimizing cell trajectory mapping under environmentally altered conditions, we trained MotGen on a comprehensive statistical dataset derived from real image data. Our experimental results demonstrate MotGen's ability to capture motility dynamics from real bacterial populations with low mean absolute error in both simulated and real datasets. MotGen allows us to approach optimal swimming conditions for desired motility statistics in real-time. MotGen's potential extends to practical biomedical applications, including immune response prediction, by providing imputation of bacterial motility patterns based on external environmental conditions. Our short-term, in-situ interventions for controlling motility behavior offer a promising foundation for the development of bacteria-based biomedical applications.

AVAILABILITY AND IMPLEMENTATION

MotGen is presented as a combination of Matlab image analysis code and a machine learning workflow in Python. Codes are available at https://github.com/bgmseo/MotGen, for cell tracking and implementation of trained models to generate bacterial motility statistics.

Nine (not so simple) steps: a practical guide to using machine learning in microbial ecology

Due to the complex nature of microbiome data, the field of microbial ecology has many current and potential uses for machine learning (ML) modeling. With the increased use of predictive ML models across many disciplines, including microbial ecology, there is extensive published information on the specific ML algorithms available and how those algorithms have been applied. Thus, our goal is not to summarize the breadth of ML models available or compare their performances. Rather, our goal is to provide more concrete and actionable information to guide microbial ecologists in how to select, run, and interpret ML algorithms to predict the taxa or genes associated with particular sample categories or environmental gradients of interest. Such microbial data often have unique characteristics that require careful consideration of how to apply ML models and how to interpret the associated results. This review is intended for practicing microbial ecologists who may be unfamiliar with some of the intricacies of ML models. We provide examples and discuss common opportunities and pitfalls specific to applying ML models to the types of data sets most frequently collected by microbial ecologists.

An Assessment of Human Opportunistic Pathogenic Bacteria on Daily Necessities in Nanjing City during Plum Rain Season

The plum rain season is a special climatic phenomenon in east Asia, which is characterized by persistent rainfall, a high temperature, and humidity, providing suitable environmental conditions for certain pathogenic bacteria, thus increasing the incidence of respiratory, gastrointestinal, and urinary diseases. However, studies on human opportunistic pathogenic bacteria communities during the plum rain season are still limited. In this study, the characteristics of human opportunistic pathogenic bacterial communities on daily necessities during the non-plum and plum rain seasons were investigated using high-throughput sequencing technology. The results revealed that the relative abundance of human opportunistic pathogenic bacteria was higher in the plum rain season (cotton cloth: 2.469%, electric bicycles: 0.724%, rice: 3.737%, and washbasins: 5.005%) than in the non-plum rain season (cotton cloth: 1.425%, electric bicycles: 0.601%, rice: 2.426%, and washbasins: 4.801%). Both temperature and relative humidity affected human opportunistic pathogenic bacterial communities. Stochastic processes dominated the assembly process of human opportunistic pathogenic bacterial communities, and undominated processes prevailed. The stability of the co-occurrence network was higher in the non-plum rain season than that in the plum rain season. In addition, the proportion of deterministic processes showed the same trend as the complexity of the co-occurrence network.

How to Provide Nitrite Robustly for Anaerobic Ammonium Oxidation in Mainstream Nitrogen Removal

Innovation in decarbonizing wastewater treatment is urgent in response to global climate change. The practical implementation of anaerobic ammonium oxidation (anammox) treating domestic wastewater is the key to reconciling carbon-neutral management of wastewater treatment with sustainable development. Nitrite availability is the prerequisite of the anammox reaction, but how to achieve robust nitrite supply and accumulation for mainstream systems remains elusive. This work presents a state-of-the-art review on the recent advances in nitrite supply for mainstream anammox, paying special attention to available pathways (forward-going (from ammonium to nitrite) and backward-going (from nitrate to nitrite)), key controlling strategies, and physiological and ecological characteristics of functional microorganisms involved in nitrite supply. First, we comprehensively assessed the mainstream nitrite-oxidizing bacteria control methods, outlining that these technologies are transitioning to technologies possessing multiple selective pressures (such as intermittent aeration and membrane-aerated biological reactor), integrating side stream treatment (such as free ammonia/free nitrous acid suppression in recirculated sludge treatment), and maintaining high activity of ammonia-oxidizing bacteria and anammox bacteria for competing oxygen and nitrite with nitrite-oxidizing bacteria. We then highlight emerging strategies of nitrite supply, including the nitrite production driven by novel ammonia-oxidizing microbes (ammonia-oxidizing archaea and complete ammonia oxidation bacteria) and nitrate reduction pathways (partial denitrification and nitrate-dependent anaerobic methane oxidation). The resources requirement of different mainstream nitrite supply pathways is analyzed, and a hybrid nitrite supply pathway by combining partial nitrification and nitrate reduction is encouraged. Moreover, data-driven modeling of a mainstream nitrite supply process as well as proactive microbiome management is proposed in the hope of achieving mainstream nitrite supply in practical application. Finally, the existing challenges and further perspectives are highlighted, i.e., investigation of nitrite-supplying bacteria, the scaling-up of hybrid nitrite supply technologies from laboratory to practical implementation under real conditions, and the data-driven management for the stable performance of mainstream nitrite supply. The fundamental insights in this review aim to inspire and advance our understanding about how to provide nitrite robustly for mainstream anammox and shed light on important obstacles warranting further settlement.

Taxonomic and environmental distribution of bacterial amino acid auxotrophies

Many microorganisms are auxotrophic-unable to synthesize the compounds they require for growth. With this work, we quantify the prevalence of amino acid auxotrophies across a broad diversity of bacteria and habitats. We predicted the amino acid biosynthetic capabilities of 26,277 unique bacterial genomes spanning 12 phyla using a metabolic pathway model validated with empirical data. Amino acid auxotrophy is widespread across bacterial phyla, but we conservatively estimate that the majority of taxa (78.4%) are able to synthesize all amino acids. Our estimates indicate that amino acid auxotrophies are more prevalent among obligate intracellular parasites and in free-living taxa with genomic attributes characteristic of 'streamlined' life history strategies. We predicted the amino acid biosynthetic capabilities of bacterial communities found in 12 unique habitats to investigate environmental associations with auxotrophy, using data compiled from 3813 samples spanning major aquatic, terrestrial, and engineered environments. Auxotrophic taxa were more abundant in host-associated environments (including the human oral cavity and gut) and in fermented food products, with auxotrophic taxa being relatively rare in soil and aquatic systems. Overall, this work contributes to a more complete understanding of amino acid auxotrophy across the bacterial tree of life and the ecological contexts in which auxotrophy can be a successful strategy.

Bacterial genome size and gene functional diversity negatively correlate with taxonomic diversity along a pH gradient

Bacterial gene repertoires reflect adaptive strategies, contribute to ecosystem functioning and are limited by genome size. However, gene functional diversity does not necessarily correlate with taxonomic diversity because average genome size may vary by community. Here, we analyse gene functional diversity (by shotgun metagenomics) and taxonomic diversity (by 16S rRNA gene amplicon sequencing) to investigate soil bacterial communities along a natural pH gradient in 12 tropical, subtropical, and temperate forests. We find that bacterial average genome size and gene functional diversity decrease, whereas taxonomic diversity increases, as soil pH rises from acid to neutral; as a result, bacterial taxonomic and functional diversity are negatively correlated. The gene repertoire of acid-adapted oligotrophs is enriched in functions of signal transduction, cell motility, secretion system, and degradation of complex compounds, while that of neutral pH-adapted copiotrophs is enriched in functions of energy metabolism and membrane transport. Our results indicate that a mismatch between taxonomic and functional diversity can arise when environmental factors (such as pH) select for adaptive strategies that affect genome size distributions.

Multi-omics study of sulfur metabolism affecting functional microbial community succession during aerobic solid-state fermentation

Microbial-mediated sulfur metabolism is closely related to carbon and nitrogen metabolism in natural biological systems. In this study, the effects of sulfur metabolism on microbial communities and functional enzyme succession were investigated based on integrated multi-omics by adding sulfur-containing compounds to aerobic fermentation systems. Sulfur powder was oxidized to S2O32- and subsequently to SO42- by the microbial sulfur-oxidizing system, which lowered the pH to 7.5 on day 7. The decrease in pH resulted in Planifilum (secreted S8, M17 and M32 proteases) losing its competitive advantage, whereas Novibacillus (secreted M14 and M19 metalloproteases) became dominant. Structural proteomics indicated that the surface of Novibacillus proteases has more negatively charged amino acid residues that help maintain protein stability at low pH. These findings aid understanding of the effects of sulfur metabolism on fermentation and the mechanism of microbial adaptation after pH reduction, providing new perspectives on the optimization of fermentation processes.

Auxin-producing bacteria promote barley rhizosheath formation

The rhizosheath, or the layer of soil closely adhering to roots, can help plants to tolerate drought under moderate soil drying conditions. Rhizosheath formation is the result of poorly understood interactions between root exudates, microbes, and soil conditions. Here, we study the roles played by the soil microbiota in rhizosheath formation in barley (a dry crop). We show that barley rhizosheath formation is greater in acid soil than in alkaline soil, and inoculation with microbiota from acid soil enhances rhizosheath formation in alkaline soil. The rhizosheath-promoting activity is associated with the presence of Flavobacteriaceae and Paenibacillaceae bacteria that express genes for biosynthesis of indole-3-acetic acid (IAA, a common auxin), as determined by metagenomics and metatranscriptomics. Two bacterial strains isolated from rhizosheath (Chryseobacterium culicis and Paenibacillus polymyxa) produce IAA and enhance barley rhizosheath formation, while their IAA-defective mutants are unable to promote rhizosheath formation. Co-inoculation with the IAA-producing strains enhances barley grain yield in field experiments through an increase in spike number. Our findings contribute to our understanding of barley rhizosheath formation, and suggest potential strategies for crop improvement.