Environmental fluctuations and their effects on microbial communities, populations and individuals

Temperature perception by ER UPR promotes preventive innate immunity and longevity

Microbial infectivity increases with rising environmental temperature, heightening the risk of infection to host organisms. The host's basal immunity is activated accordingly to mitigate upcoming pathogenic threats; still, how animals sense temperature elevation to adjust their preventive immune response remains elusive. This study reports that high temperature enhances innate immunity differently from pathogen infection. Unlike pathogen invasion requiring the mitochondrial unfolded protein response (UPR), high temperature engages the endoplasmic reticulum (ER) UPR to trigger the innate immune response. Furthermore, chronic activation of the XBP-1 UPR branch represses nucleolar ribosome biogenesis, a highly energy-consuming process, leading to lipid accumulation. The subsequent increase in oleic acid promotes the activation of the PMK-1 immune pathway. Additionally, ribosome biogenesis was identified as a regulator of longevity, wherein its impact is dependent on lipid metabolism and innate immunity. Collectively, our findings reveal the crucial role of ER-nucleolus crosstalk in shaping preventive immune responses and lifespan regulation.

Identification of bacterial communities associated with needle mushroom (Flammulina filiformis) and its production environment

Flammulina filiformis is an important edible and medicinal mushroom widely cultivated in East Asia, with its quality and health strongly influenced by associated microbial communities. However, limited data exist on the bacterial communities associated with F. filiformis cultivation in Chinese farms. This study investigated bacterial communities associated with F. filiformis and its production environment using high-throughput 16S rRNA gene amplicon sequencing and culture-dependent methods. A total of 42 samples were collected from farms in Jilin and Guizhou provinces, China, for microbial community profiling. The analysis revealed diverse bacterial phyla, including Proteobacteria, Firmicutes, Bacteroidetes, Actinobacteria, and Cyanobacteria. Genera such as Pseudomonas, Lactobacillus, Acinetobacter, Flavobacterium, and Phyllobacterium were identified, with notable regional variations in the relative abundance of Pseudomonas and Lactobacillus. Pathogenic species, including Pseudomonas tolaasii, Ewingella americana, Stenotrophomonas maltophilia, Pseudomonas sp., Lelliottia amnigena, and Janthinobacterium lividum, were identified through phenotypic, biochemical, and molecular analyses. Pathogenicity tests confirmed the disease-causing potential of P. tolaasii, E. americana, and J. lividum in F. filiformis. These findings highlight regional differences in bacterial community composition and emphasize the need for tailored management practices. This study contributes to safe, high-quality mushroom cultivation and provides insights into improved cultivation practices, including Mushroom Good Agricultural Practices (MGAP).

Optimal resource allocation in micro-organisms under periodic nutrient fluctuations

Although microorganisms often live in dynamic environments, most studies, both experimental and theoretical, are carried out under static conditions. In this work, we investigate the issue of optimal resource allocation in bacteria growing in periodic environments. We consider a dynamic model describing the microbial metabolism under varying conditions, involving a control variable quantifying the protein precursors allocation. Our objective is to determine the optimal strategies maximizing the long-term growth of cells under a piecewise-constant periodic environment. Firstly, we perform a theoretical analysis of the resulting optimal control problem (OCP), based on the application the Pontryagin's Maximum Principle (PMP). We determine that the structure of the optimal control must be bang-bang, with possibly some singular arcs corresponding to optimal equilibria of the system. If the control presents singular arcs, then these can only be reached and left through chattering arcs. We also use a direct optimization method, implemented in the BOCOP software, to solve the studied OCP. Our study reveals that the optimal solution over a large time horizon is related to the one over a single period of the varying environment with periodic constraints. Moreover, we observe that the maximal average growth rate attainable under periodic conditions can be higher than the one under a constant environment. We further extend our analysis to conduct a qualitative comparison between the predictions from our model and some recent biological experiments on E. coli. This analysis particularly highlights the mechanisms of action of the ppGpp signaling molecule, thus providing relevant explanations of the experimental observations. In conclusion, our study corroborates previous research indicating that this molecule plays a crucial role in the regulation of resource allocation of protein precursors in E. coli.

An ecological and stochastic perspective on persisters resuscitation

Resistance, tolerance, and persistence to antibiotics have mainly been studied at the level of a single microbial isolate. However, in recent years it has become evident that microbial interactions play a role in determining the success of antibiotic treatments, in particular by influencing the occurrence of persistence and tolerance within a population. Additionally, the challenge of resuscitation (the capability of a population to revive after antibiotic exposure) and pathogen clearance are strongly linked to the small size of the surviving population and to the presence of fluctuations in cell counts. Indeed, while large population dynamics can be considered deterministic, small populations are influenced by stochastic processes, making their behaviour less predictable. Our study argues that microbe-microbe interactions within a community affect the mode, tempo, and success of persister resuscitation and that these are further influenced by noise. To this aim, we developed a theoretical model of a three-member microbial community and analysed the role of cell-to-cell interactions on pathogen clearance, using both deterministic and stochastic simulations. Our findings highlight the importance of ecological interactions and population size fluctuations (and hence the underlying cellular mechanisms) in determining the resilience of microbial populations following antibiotic treatment.

Key active mercury methylating microorganisms and their synergistic effects on methylmercury production in paddy soils

Rice contamination with neurotoxic methylmercury (MeHg) from paddy soils is an escalating global concern. Identifying the microorganisms responsible for mercury (Hg) methylation in these soils is essential for controlling Hg contamination in the food chain and mitigating health impacts. Current research often focuses on total Hg-methylating microorganisms, overlooking the contributions of active ones, which can lead to either overestimating or neglecting the specific roles of microorganisms in Hg methylation within paddy soils. In this study, active Hg-methylating microorganisms in paddy soils were identified using a combination of DNA-SIP, Hg isotope labelling, and Hg methylation gene sequencing techniques. Our findings revealed that Geobacter and Anaerolinea are pivotal active Hg-methylating microorganisms across a contamination gradient in paddy soils. Transcriptomic analysis of soils from major rice-producing provinces in China confirmed the widespread and synergistic involvement of these microorganisms. Microbial incubation further validated their interaction significantly enhances Hg methylation, with Me198Hg concentrations increasing 2.8-fold compared to Geobacter alone and 5.2-fold compared to Anaerolinea alone. These findings enhance our understanding of microbial Hg methylation in paddy soils, providing critical insights for accurately predicting soil MeHg load, rice grain MeHg contamination, and human MeHg exposure risks.

Enhanced bioremediation of bensulfuron-methyl contaminated soil by Hansschlegelia zhihuaiae S113: Metabolic pathways and bacterial community structure

Bensulfuron-methyl (BSM), a widely used herbicide, can persist in soil and damag sensitive crops. Microbial degradation, supplemented with exogenous additives, provides an effective strategy to enhance BSM breakdown. Hansschlegelia zhihuaiae S113 has been shown to efficiently degrade this sulfonylurea herbicide. However, depending solely on a single strain for degradation proves inefficient and unlikely to achieve ideal remediation in practical applications. This study assessed the impact of various carbon sources on the degradation efficiency of S113 in BSM-polluted soil. Among these, glucose was the most effective, achieving a 98.7 % degradation rate after 9 d of inoculation. In addition, seven intermediates were detected during BSM degradation in soil through the cleavage of the phenyl ring ester bond, the pyrimidine rings, and urea bridge peptide bond, among other pathways. 2-amino-4,6-dimethoxy pyrimidine (ADMP), and 2-(aminosulfonylmethyl)-methyl benzoate(MSMB) were the primary intermediates. These metabolites were less toxic to maize, sorghum, and bacteria than the BSM. Community structure analysis indicated that variations in exogenous carbon sources and environmental pollutants significantly improved the ecological functions of soil microbial communities, enhancing pollutant degradation. Addition of carbon sources notably affected soil microbial community structure, modifying metabolic activities and interaction patterns. Specifically, glucose substantially increased the richness and diversity of soil bacterial communities. These findings offer valuable insights for field remediation practices and contributed to the development of more robust soil pollution management strategies.

Differences in Gut Microbes Across Age and Sex Linked to Metabolism and Microbial Stability in a Hibernating Mammal

The gut microbiome has a well-documented relationship with host fitness, physiology, and behavior. However, most of what is known comes from captive animals where diets and environments are more homogeneous or controlled. Studies in wild populations that experience dynamic environments and have natural life history variation are less common but are key to understanding the drivers of variation in the gut microbiome. Here we examine a wild population of yellow-bellied marmots (Marmota flaviventer), an obligate winter hibernator, to quantify multivariate associations between host-associated factors (e.g., age, sex, environmental harshness, and social behavior) and gut microbial composition. Across 5 years and 143 individuals, we found that males had a higher relative abundance of microbes associated with mass gain and cellulose digestion, which suggests a metabolic investment in mass gain (such as phylum Firmicutes and family Lachnospiraceae). By contrast, females had higher relative abundances of microbes associated with inflammation and metabolism (from microbial groups such as Tenericutes and Ruminococcus), possibly reflecting the importance of lactation and offspring investment. Post hoc analyses of lactating females showed a negative relationship with the abundance of microbes associated with mass gain but a positive relationship with microbes associated with metabolic energy, suggesting a trade-off between investment in pups and maternal mass gain. Older animals also had reduced Proteobacteria relative abundance, a phylum associated with reduced inflammation. Results demonstrate that sex and age-based traits, not sociality or environmental harshness, are associated with microbe-mediated metabolism and inflammation in a wild, hibernating mammal.

Using machine learning to identify environmental factors that collectively determine microbial community structure of activated sludge

Activated sludge (AS) microbial communities are influenced by various environmental variables. However, a comprehensive analysis of how these variables jointly and nonlinearly shape the AS microbial community remains challenging. In this study, we employed advanced machine learning techniques to elucidate the collective effects of environmental variables on the structure and function of AS microbial communities. Applying Dirichlet multinomial mixtures analysis to 311 global AS samples, we identified four distinct microbial community types (AS-types), each characterized by unique microbial compositions and metabolic profiles. We used 14 classical linear and nonlinear machine learning methods to select a baseline model. The extremely randomized trees demonstrated optimal performance in learning the relationship between environmental factors and AS types (with an accuracy of 71.43%). Feature selection identified critical environmental factors and their importance rankings, including latitude (Lat), longitude (Long), precipitation during sampling (Precip), solids retention time (SRT), effluent total nitrogen (Effluent TN), average temperature during sampling month (Avg Temp), mixed liquor temperature (Mixed Temp), influent biochemical oxygen demand (Influent BOD), and annual precipitation (Annual Precip). Significantly, Lat, Long, Precip, Avg Temp, and Annual Precip, influenced metabolic variations among AS types. These findings emphasize the pivotal role of environmental variables in shaping microbial community structures and enhancing metabolic pathways within activated sludge. Our study encourages the application of machine learning techniques to design artificial activated sludge microbial communities for specific environmental purposes.

Isolation and identification of aerobic and anaerobic bacteria from the feces of wild Korean water deer (Hydropotes inermis argyropus)

IMPORTANCE

Understanding the microbial diversity within the gastrointestinal tract of wild Korean water deer (KWD; Hydropotes inermis argyropus) is essential for gaining insights into their health and ecological interactions.

OBJECTIVE

This study aims to isolate and identify aerobic and anaerobic bacterial species in the feces of wild KWD.

METHODS

Fecal samples were collected from 55 wild KWD of varying age and sex. Aerobic bacteria were cultured at 37°C for 24-48 h under standard conditions, whereas anaerobic bacteria were cultured at 37°C for 48-72 h in an anaerobic environment. Bacterial identification was conducted using DNA extraction and polymerase chain reaction amplification targeting the 16S rRNA gene.

RESULTS

The predominant aerobic bacteria identified belonged to the Firmicutes (58.18%) and Proteobacteria (41.82%) phyla, with Escherichia coli (31.82%) and Bacillus cereus (31.82%) being the most common species. Among anaerobic bacteria, most belonged to the Firmicutes (71.03%), Proteobacteria (27.10%), and Fusobacteriota (1.87%) phyla, with Paraclostridium bifermentans (28.97%) and E. coli (22.43%) being the most prevalent species. Other frequently identified anaerobic species were Fusobacterium varium, Lactococcus garvieae, Terrisporobacter glycolicus, Enterococcus faecalis, and Clostridium sporogenes.

CONCLUSIONS AND RELEVANCE

Our findings indicate a diverse microbial community in the feces of water deer, offering valuable insights into their gut microbiota and its potential implications for health and ecology.

Growth of sulfate-reducing Desulfobacterota and Bacillota at periodic oxygen stress of 50% air-O2 saturation

BACKGROUND

Sulfate-reducing bacteria (SRB) are frequently encountered in anoxic-to-oxic transition zones, where they are transiently exposed to microoxic or even oxic conditions on a regular basis. This can be marine tidal sediments, microbial mats, and freshwater wetlands like peatlands. In the latter, a cryptic but highly active sulfur cycle supports their anaerobic activity. Here, we aimed for a better understanding of how SRB responds to periodically fluctuating redox regimes.

RESULTS

To mimic these fluctuating redox conditions, a bioreactor was inoculated with peat soil supporting cryptic sulfur cycling and consecutively exposed to oxic (one week) and anoxic (four weeks) phases over a period of > 200 days. SRB affiliated to the genus Desulfosporosinus (Bacillota) and the families Syntrophobacteraceae, Desulfomonilaceae, Desulfocapsaceae, and Desulfovibrionaceae (Desulfobacterota) successively established growing populations (up to 2.9% relative abundance) despite weekly periods of oxygen exposures at 133 µM (50% air saturation). Adaptation mechanisms were analyzed by genome-centric metatranscriptomics. Despite a global drop in gene expression during oxic phases, the perpetuation of gene expression for energy metabolism was observed for all SRBs. The transcriptional response pattern for oxygen resistance was differentiated across individual SRBs, indicating different adaptation strategies. Most SRB transcribed differing sets of genes for oxygen consumption, reactive oxygen species detoxification, and repair of oxidized proteins as a response to the periodical redox switch from anoxic to oxic conditions. Noteworthy, a Desulfosporosinus, a Desulfovibrionaceaea, and a Desulfocapsaceaea representative maintained high transcript levels of genes encoding oxygen defense proteins even under anoxic conditions, while representing dominant SRB populations after half a year of bioreactor operation.

CONCLUSIONS

In situ-relevant peatland SRB established large populations despite periodic one-week oxygen levels that are one order of magnitude higher than known to be tolerated by pure cultures of SRB. The observed decrease in gene expression regulation may be key to withstand periodically occurring changes in redox regimes in these otherwise strictly anaerobic microorganisms. Our study provides important insights into the stress response of SRB that drives sulfur cycling at oxic-anoxic interphases. Video Abstract.

Metatranscriptomic insights into the dengue patient blood microbiome: Enhanced microbial diversity and metabolic activity in severe patients

BACKGROUND

Dengue is the most re-emergent infection, with approximately 100 million new cases reported annually, yet no effective treatment or vaccine exists. Here, we aim to define the microbial community structure and their functional profiles in the dengue positive patients with varying disease severity.

METHODOLOGY/PRINCIPAL FINDINGS

Hospital admitted 112 dengue-positive patients blood samples were analyzed by dual RNA-sequencing to simultaneously identify the transcriptionally active microbes (TAMs), their expressed genes and associated pathways. Results highlight that patients with severe dengue exhibited increased microbial diversity and presence of opportunistic species (unique and core) which includes Bacillus cereus, Burkholderia pseudomallei, Streptococcus suis, and Serratia marcescens. The functional profile analysis revealed enriched metabolic pathways such as protein degradation, nucleotide biosynthesis, ion transport, cell shape integrity, and ATP formation in severe cases, indicating the high energy demands and adaptability of these microbes.

CONCLUSION

Our metatranscriptomic approach provides a species-level characterization of blood microbiome composition and reveals a heightened diversity of TAMs in patients with severe dengue, underscoring the need for further research into the role of blood microbiota in disease progression. Comparing the microbial signatures across the severity classes early in the disease offers unique potential for convenient and early diagnosis of dengue infection.

Escape from a metastable state in non-Markovian population dynamics

We study the long-time dynamics in non-Markovian single-population stochastic models, where one or more reactions are modeled as a stochastic process with a fat-tailed nonexponential distribution of waiting times, mimicking long-term memory. We focus on three prototypical examples: genetic switching, population establishment, and population extinction, all with nonexponential production rates. The system is studied in two regimes. In the first, the distribution of waiting times has a finite mean. Here, the system approaches a (quasi)stationary steady state at long times, and we develop a general Wentzel-Kramers-Brillouin approach for these non-Markovian systems. We derive explicit results for the mean population size and mean escape time from the metastable state of the stochastic dynamics. In this realm, we reveal that for sufficiently strong memory, a memory-induced (meta)stable state can emerge in the system. In the second regime, the waiting time distribution is assumed to have an infinite mean. Here, for bistable systems we find two distinct scaling regimes, separated by an exponentially long time which may strongly depend on the initial conditions of the system.

Evolution of pH-sensitive transcription termination in Escherichia coli during adaptation to repeated long-term starvation

Fluctuating environments that consist of regular cycles of co-occurring stress are a common challenge faced by cellular populations. For a population to thrive in constantly changing conditions, an ability to coordinate a rapid cellular response is essential. Here, we identify a mutation conferring an arginine-to-histidine (Arg to His) substitution in the transcription terminator Rho. The rho R109H mutation frequently arose in Escherichia coli populations experimentally evolved under repeated long-term starvation conditions, during which the accumulation of metabolic waste followed by transfer into fresh media results in drastic environmental pH fluctuations associated with feast and famine. Metagenomic sequencing revealed that populations containing the rho mutation also possess putative loss-of-function mutations in ydcI, which encodes a recently characterized transcription factor associated with pH homeostasis. Genetic reconstructions of these mutations show that the rho allele confers plasticity via an alkaline-induced reduction of Rho function that, when found in tandem with a ΔydcI allele, leads to intracellular alkalization and genetic assimilation of Rho mutant function. We further identify Arg to His substitutions at analogous sites in rho alleles from species that regularly experience neutral to alkaline pH fluctuations in their environments. Our results suggest that Arg to His substitutions in Rho may serve to rapidly coordinate complex physiological responses through pH sensing and shed light on how cellular populations use environmental cues to coordinate rapid responses to complex, fluctuating environments.

The rise and future of CRISPR-based approaches for high-throughput genomics

Clustered regularly interspaced short palindromic repeats (CRISPR) has revolutionized the field of genome editing. To circumvent the permanent modifications made by traditional CRISPR techniques and facilitate the study of both essential and nonessential genes, CRISPR interference (CRISPRi) was developed. This gene-silencing technique employs a deactivated Cas effector protein and a guide RNA to block transcription initiation or elongation. Continuous improvements and a better understanding of the mechanism of CRISPRi have expanded its scope, facilitating genome-wide high-throughput screens to investigate the genetic basis of phenotypes. Additionally, emerging CRISPR-based alternatives have further expanded the possibilities for genetic screening. This review delves into the mechanism of CRISPRi, compares it with other high-throughput gene-perturbation techniques, and highlights its superior capacities for studying complex microbial traits. We also explore the evolution of CRISPRi, emphasizing enhancements that have increased its capabilities, including multiplexing, inducibility, titratability, predictable knockdown efficacy, and adaptability to nonmodel microorganisms. Beyond CRISPRi, we discuss CRISPR activation, RNA-targeting CRISPR systems, and single-nucleotide resolution perturbation techniques for their potential in genome-wide high-throughput screens in microorganisms. Collectively, this review gives a comprehensive overview of the general workflow of a genome-wide CRISPRi screen, with an extensive discussion of strengths and weaknesses, future directions, and potential alternatives.

The evolution of autonomy from two cooperative specialists in fluctuating environments

From microbes to humans, organisms perform numerous tasks for their survival, including food acquisition, migration, and reproduction. A complex biological task can be performed by either an autonomous organism or by cooperation among several specialized organisms. However, it remains unclear how autonomy and cooperation evolutionarily switch. Specifically, it remains unclear whether and how cooperative specialists can repair deleted genes through direct genetic exchange, thereby regaining metabolic autonomy. Here, we address this question by experimentally evolving a mutualistic microbial consortium composed of two specialists that cooperatively degrade naphthalene. We observed that autonomous genotypes capable of performing the entire naphthalene degradation pathway evolved from two cooperative specialists and dominated the community. This evolutionary transition was driven by the horizontal gene transfer (HGT) between the two specialists. However, this evolution was exclusively observed in the fluctuating environment alternately supplied with naphthalene and pyruvate, where mutualism and competition between the two specialists alternated. The naphthalene-supplied environment exerted selective pressure that favors the expansion of autonomous genotypes. The pyruvate-supplied environment promoted the coexistence and cell density of the cooperative specialists, thereby increasing the likelihood of HGT. Using a mathematical model, we quantitatively demonstrate that environmental fluctuations facilitate the evolution of autonomy through HGT when the relative growth rate and carrying capacity of the cooperative specialists allow enhanced coexistence and higher cell density in the competitive environment. Together, our results demonstrate that cooperative specialists can repair deleted genes through a direct genetic exchange under specific conditions, thereby regaining metabolic autonomy.

Comparison of Six Measures of Genetic Similarity of Interspecific Brassicaceae Hybrids F2 Generation and Their Parental Forms Estimated on the Basis of ISSR Markers

Genetic similarity determines the extent to which two genotypes share common genetic material. It can be measured in various ways, such as by comparing DNA sequences, proteins, or other genetic markers. The significance of genetic similarity is multifaceted and encompasses various fields, including evolutionary biology, medicine, forensic science, animal and plant breeding, and anthropology. Genetic similarity is an important concept with wide application across different scientific disciplines. The research material included 21 rapeseed genotypes (ten interspecific Brassicaceae hybrids of F2 generation and 11 of their parental forms) and 146 alleles obtained using 21 ISSR molecular markers. In the presented study, six measures for calculating genetic similarity were compared: Euclidean, Jaccard, Kulczyński, Sokal and Michener, Nei, and Rogers. Genetic similarity values were estimated between all pairs of examined genotypes using the six measures proposed above. For each genetic similarity measure, the average, minimum, maximum values, and coefficient of variation were calculated. Correlation coefficients between the genetic similarity values obtained from each measure were determined. The obtained genetic similarity coefficients were used for the hierarchical clustering of objects using the unweighted pair group method with an arithmetic mean. A multiple regression model was written for each method, where the independent variables were the remaining methods. For each model, the coefficient of multiple determination was calculated. Genetic similarity values ranged from 0.486 to 0.993 (for the Euclidean method), from 0.157 to 0.986 (for the Jaccard method), from 0.275 to 0.993 (for the Kulczyński method), from 0.272 to 0.993 (for the Nei method), from 0.801 to 1.000 (for the Rogers method) and from 0.486 to 0.993 (for the Sokal and Michener method). The results indicate that the research material was divided into two identical groups using any of the proposed methods despite differences in the values of genetic similarity coefficients. Two of the presented measures of genetic similarity (the Sokal and Michener method and the Euclidean method) were the same.

Overcoming toxicity: why boom-and-bust cycles are good for non-antagonistic microbes

Antagonistic interactions are critical determinants of microbial community stability and composition, offering host benefits such as pathogen protection and providing avenues for antimicrobial control. While the ability to eliminate competitors confers an advantage to antagonistic microbes, it often incurs a fitness cost. Consequently, many microbes only produce toxins or engage in antagonistic behavior in response to specific cues like population density or environmental stress. In laboratory settings, antagonistic microbes typically dominate over sensitive ones, raising the question of why both antagonistic and non-antagonistic microbes are found in natural environments and host microbiomes. Here, using both theoretical models and experiments with killer strains of Saccharomyces cerevisiae , we show that boom-and-bust dynamics caused by temporal environmental fluctuations can favor non-antagonistic microbes that do not incur the growth rate cost of toxin production. Additionally, using control theory, we derive bounds on the competitive performance and identify optimal regulatory toxin-production strategies in various boom-and-bust environments where population dilutions occur either deterministically or stochastically over time. Our findings offer a new perspective on how both antagonistic and non-antagonistic microbes can thrive under varying environmental conditions.

Longitudinal Analysis of Urban Stormwater Microbiome and Resistome from Watersheds with and without Green Infrastructure using Long-Read Sequencing

Since stormwater conveys a variety of contaminants into water bodies, green infrastructure (GI) is increasingly being adopted as an on-site treatment solution in addition to controlling peak flows. The purpose of this study was to identify differences in microbial water quality of stormwater in watersheds retrofitted with GI vs. those without GI. Considering stormwater is recently recognized as a contributor to the antibiotic resistance (AR) threat, another goal of this study was to characterize changes in the microbiome and collection of AR genes (resistome) of urban stormwater with season, rainfall characteristics, and fecal contamination. MinION long-read sequencing was used to analyze stormwater microbiome and resistome from watersheds with and without GI in Columbus, Ohio, United States, over 18 months. We characterized fecal contamination in stormwater via culturing Escherichia coli and with molecular microbial source tracking (MST) to identify sources of fecal contamination. Overall, season and storm event (rainfall) characteristics had the strongest relationships with changes in the stormwater microbiome and resistome. We found no significant differences in microbial water quality or the microbiome of stormwater in watersheds with and without GI implemented. However, there were differences between the communities of microorganisms hosting antibiotic resistance genes (ARGs) in stormwater from watersheds with and without GI, indicating the potential sensitivity of AR bacteria to treatment. Stormwater was contaminated with high concentrations of human-associated fecal bacterial genes, and the ARG host bacterial community had considerable similarities to human feces/wastewater. We also identified 15 potential pathogens hosting ARGs in these stormwater resistome, including vancomycin-resistant Enterococcus faecium (VRE) and multidrug-resistant Pseudomonas aeruginosa. In summary, urban stormwater is highly contaminated and has a great potential to spread AR and microbial hazards to nearby environments. This study presents the most comprehensive analysis of stormwater microbiome and resistome to date, which is crucial to understanding the potential microbial risk from this matrix. This information can be used to guide future public health policy, stormwater reuse programs, and urban runoff treatment initiatives.

Effects of experimental canopy openness on wood-inhabiting fungal fruiting diversity across succession

While the succession of terrestrial plant communities is well studied, less is known about succession on dead wood, especially how it is affected by environmental factors. While temperate forests face increasing canopy mortality, which causes considerable changes in microclimates, it remains unclear how canopy openness affects fungal succession. Here, we used a large real-world experiment to study the effect of closed and opened canopy on treatment-based alpha and beta fungal fruiting diversity. We found increasing diversity in early and decreasing diversity at later stages of succession under both canopies, with a stronger decrease under open canopies. However, the slopes of the diversity versus time relationships did not differ significantly between canopy treatments. The community dissimilarity remained mainly stable between canopies at ca. 25% of species exclusively associated with either canopy treatment. Species exclusive in either canopy treatment showed very low number of occupied objects compared to species occurring in both treatments. Our study showed that canopy loss subtly affected fungal fruiting succession on dead wood, suggesting that most species in the local species pool are specialized or can tolerate variable conditions. Our study indicates that the fruiting of the fungal community on dead wood is resilient against the predicted increase in canopy loss in temperate forests.

Consistent community assembly but contingent species pool effects drive β-diversity patterns of multiple microbial groups in desert biocrust systems

One of the key goals of ecology is to understand how communities are assembled. The species co-existence theory suggests that community β-diversity is influenced by species pool and community assembly processes, such as environmental filtering, dispersal events, ecological drift and biotic interactions. However, it remains unclear whether there are similar β-diversity patterns among different soil microbial groups and whether all these mechanisms play significant roles in mediating β-diversity patterns. By conducting a broad survey across Chinese deserts, we aimed to address these questions by investing biological soil crusts (biocrusts). Through amplicon-sequencing, we acquired β-diversity data for multiple microbial groups, that is, soil total bacteria, diazotrophs, phoD-harbouring taxa, and fungi. Our results have shown varying distance decay rates of β-diversity across microbial groups, with soil total bacteria showing a weaker distance-decay relationship than other groups. The impact of the species pool on community β-diversity varied across microbial groups, with soil total bacteria and diazotrophs being significantly influenced. While the contributions of specific assembly processes to community β-diversity patterns varied among different microbial groups, significant effects of local community assembly processes on β-diversity patterns were consistently observed across all groups. Homogenous selection and dispersal limitation emerged as crucial processes for all groups. Precipitation and soil C:P were the key factors mediating β-diversity for all groups. This study has substantially advanced our understanding of how the communities of multiple microbial groups are structured in desert biocrust systems.

Exploring long-term retention and reactivation of micropollutant biodegradation capacity

The factors limiting micropollutant biodegradation in the environment and how to stimulate this process have often been investigated. However, little information is available on the capacity of microbial communities to retain micropollutant biodegradation capacity in the absence of micropollutants or to reactivate micropollutant biodegradation in systems with fluctuating micropollutant concentrations. This study investigated how a period of 2 months without the addition of micropollutants and other organic carbon affected micropollutant biodegradation by a micropollutant-degrading microbial community. Stimulation of micropollutant biodegradation was performed by adding different types of dissolved organic carbon (DOC)-extracted from natural sources and acetate-increasing 10 × the micropollutant concentration, and inoculating with activated sludge. The results show that the capacity to biodegrade 3 micropollutants was permanently lost. However, the biodegradation activity of 2,4-D, antipyrine, chloridazon, and its metabolites restarted when these micropollutants were re-added to the community. Threshold concentrations similar to those obtained before the period of no substrate addition were achieved, but biodegradation rates were lower for some compounds. Through the addition of high acetate concentrations (108 mg-C/L), gabapentin biodegradation activity was regained, but 2,4-D biodegradation capacity was lost. An increase of bentazon concentration from 50 to 500 µg/L was necessary for biodegradation to be reactivated. These results provide initial insights into the longevity of micropollutant biodegradation capacity in the absence of the substance and strategies for reactivating micropollutant biodegrading communities.

Biostimulation with oxygen and electron donors supports micropollutant biodegradation in an experimentally simulated nitrate-reducing aquifer

The availability of suitable electron donors and acceptors limits micropollutant natural attenuation in oligotrophic groundwater. This study investigated how electron donors with different biodegradability (humics, dextran, acetate, and ammonium), and different oxygen concentrations affect the biodegradation of 15 micropollutants (initial concentration of each micropollutant = 50 μg/L) in simulated nitrate reducing aquifers. Tests mimicking nitrate reducing field conditions showed no micropollutant biodegradation, even with electron donor amendment. However, 2,4-dichlorophenoxyacetic acid and mecoprop were biodegraded under (micro)aerobic conditions with and without electron donor addition. The highest 2,4-dichlorophenoxyacetic acid and mecoprop biodegradation rates and removal efficiencies were obtained under fully aerobic conditions with amendment of an easily biodegradable electron donor. Under microaerobic conditions, however, amendment with easily biodegradable dissolved organic carbon (DOC) inhibited micropollutant biodegradation due to competition between micropollutants and DOC for the limited oxygen available. Microbial community composition was dictated by electron acceptor availability and electron donor amendment, not by micropollutant biodegradation. Low microbial community richness and diversity led to the absence of biodegradation of the other 13 micropollutants (such as bentazon, chloridazon, and carbamazepine). Finally, adaptation and potential growth of biofilms interactively determined the location of the micropollutant removal zone relative to the point of amendment. This study provides new insight on how to stimulate in situ micropollutant biodegradation to remediate oligotrophic groundwaters as well as possible limitations of this process.

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.

Biodiversity is enhanced by sequential resource utilization and environmental fluctuations via emergent temporal niches

How natural communities maintain their remarkable biodiversity and which species survive in complex communities are central questions in ecology. Resource competition models successfully explain many phenomena but typically predict only as many species as resources can coexist. Here, we demonstrate that sequential resource utilization, or diauxie, with periodic growth cycles can support many more species than resources. We explore how communities modify their own environments by sequentially depleting resources to form sequences of temporal niches, or intermediately depleted environments. Biodiversity is enhanced when community-driven or environmental fluctuations modulate the resource depletion order and produce different temporal niches on each growth cycle. Community-driven fluctuations under constant environmental conditions are rare, but exploring them illuminates the temporal niche structure that emerges from sequential resource utilization. With environmental fluctuations, we find most communities have more stably coexisting species than resources with survivors accurately predicted by the same temporal niche structure and each following a distinct optimal strategy. Our results thus present a new niche-based approach to understanding highly diverse fluctuating communities.

Pediococcus spp.-mediated competition interaction within Daqu microbiota determines the temperature formation and metabolic profiles

Fermented microbiota is critical to the formation of microenvironment and metabolic profiles in spontaneous fermentation. Microorganisms generate a diverse array of metabolites concurrent with the release of heat energy. In the case of Daqu fermentation, the peak temperature exceeded 60°C, forming a typical high-temperature fermentation system known as high-temperature Daqu. However, microorganisms that cause the quality variation in Daqu and how they affect the functional microbiota and microenvironment in the fermentation process are not yet clear. This study adopted high-throughput sequencing and monitored the dynamic fluctuations of metabolites and environmental factors to identify the pivotal microorganism responsible for the alterations in interaction patterns of functional keystone taxa and quality decline in the fermentation system of different operational areas during the in situ fermentation process that had been mainly attributed to operational taxonomic unit (OTU)_22 (Pediococcus acidilactici). Additionally, we used isothermal microcalorimetry, plate inhibition experiments, and in vitro simulation fermentation experiments to explore the impact of Pediococcus spp. on heat generation, microorganisms, and metabolite profiles. Results showed the heat peak generated by Pediococcus spp. was significantly lower than that of Bacillus spp., filamentous fungi, and yeast. In addition, the preferential growth of P. acidilactici strain AA3 would obviously affect other strains to colonize through competition, and its metabolites made a significant impact on filamentous fungi. The addition of P. acidilactici strain AA3 in simulated fermentation would cause the loss of pyrazines and acids in metabolites. These evidences showed that the overgrowth of Pediococcus spp. greatly influenced the formation of high temperatures and compounds in solid-state fermentation systems. Our work illustrated the vital impact of interaction variability mediated by Pediococcus spp. for microbial assembly and metabolites, as well as in forming temperature. These results emphasized the functional role of Daqu microbiota in metabolites and heat production and the importance of cooperation in improving the fermentation quality.IMPORTANCEThe stable and high-quality saccharifying and fermenting starter in traditional solid-state fermentation was the prerequisite for liquor brewing. An imbalance of microbial homeostasis in fermentation can adversely impact production quality. Identification of such critical microorganisms and verifying their associations with other fermentation parameters pose a challenge in a traditional fermentation environment. To enhance the quality of spontaneous fermented products, strategies such as bioaugmentation or the control of harmful microorganisms would be employed. This work started with the differences in high-temperature Daqu metabolites to explore a series of functional microorganisms that could potentially contribute to product disparities, and found that the differences in interactions facilitated directly or indirectly by Pediococcus spp. seriously affected the development of microbial communities and metabolites, as well as the formation of the microenvironment. This study not only identified functional microbiota in Daqu that affected fermentation quality, but also demonstrated how microorganisms interact to affect the fermentation system, which would provide guidance for microbial supervision in the actual production process. Besides, the application of isothermal microcalorimetry in this study was helpful for us to understand the heat production capacity of microorganisms and their adaptability to the environment. This study presented a commendable framework for improving and controlling the quality of traditional fermentation and inspired further investigations in similar systems.

Nimble vs. torpid responders to hydration pulse duration among soil microbes

Environmental parameters vary in time, and variability is inherent in soils, where microbial activity follows precipitation pulses. The expanded pulse-reserve paradigm (EPRP) contends that arid soil microorganisms have adaptively diversified in response to pulse regimes differing in frequency and duration. To test this, we incubate Chihuahuan Desert soil microbiomes under separate treatments in which 60 h of hydration was reached with pulses of different pulse duration (PD), punctuated by intervening periods of desiccation. Using 16S rRNA gene amplicon data, we measure treatment effects on microbiome net growth, growth efficiency, diversity, and species composition, tracking the fate of 370 phylotypes (23% of those detected). Consistent with predictions, microbial diversity is a direct, saturating function of PD. Increasingly larger shifts in community composition are detected with decreasing PD, as specialist phylotypes become more prominent. One in five phylotypes whose fate was tracked responds consistently to PD, some preferring short pulses (nimble responders; NIRs) and some longer pulses (torpid responders; TORs). For pulses shorter than a day, microbiome growth efficiency is an inverse function of PD, as predicted. We conclude that PD in pulsed soil environments constitutes a major driver of microbial community assembly and function, largely consistent with the EPRP predictions.

Evolution of pH-sensitive transcription termination during adaptation to repeated long-term starvation

Fluctuating environments that consist of regular cycles of co-occurring stress are a common challenge faced by cellular populations. For a population to thrive in constantly changing conditions, an ability to coordinate a rapid cellular response is essential. Here, we identify a mutation conferring an arginine-to-histidine (Arg to His) substitution in the transcription terminator Rho. The rho R109H mutation frequently arose in E. coli populations experimentally evolved under repeated long-term starvation conditions, during which feast and famine result in drastic environmental pH fluctuations. Metagenomic sequencing revealed that populations containing the rho mutation also possess putative loss-of-function mutations in ydcI, which encodes a recently characterized transcription factor associated with pH homeostasis. Genetic reconstructions of these mutations show that the rho allele confers a plastic alkaline-induced reduction of Rho function that, when found in tandem with a ΔydcI allele, leads to intracellular alkalinization and genetic assimilation of Rho mutant function. We further identify Arg to His substitutions at analogous sites in rho alleles from species originating from fluctuating alkaline environments. Our results suggest that Arg to His substitutions in global regulators of gene expression can serve to rapidly coordinate complex responses through pH sensing and shed light on how cellular populations across the tree of life use environmental cues to coordinate rapid responses to complex, fluctuating environments.

A molecular toolkit of cross-feeding strains for engineering synthetic yeast communities

Engineered microbial consortia often have enhanced system performance and robustness compared with single-strain biomanufacturing production platforms. However, few tools are available for generating co-cultures of the model and key industrial host Saccharomyces cerevisiae. Here we engineer auxotrophic and overexpression yeast strains that can be used to create co-cultures through exchange of essential metabolites. Using these strains as modules, we engineered two- and three-member consortia using different cross-feeding architectures. Through a combination of ensemble modelling and experimentation, we explored how cellular (for example, metabolite production strength) and environmental (for example, initial population ratio, population density and extracellular supplementation) factors govern population dynamics in these systems. We tested the use of the toolkit in a division of labour biomanufacturing case study and show that it enables enhanced and tuneable antioxidant resveratrol production. We expect this toolkit to become a useful resource for a variety of applications in synthetic ecology and biomanufacturing.

Microfluidic approaches in microbial ecology

Microbial life is at the heart of many diverse environments and regulates most natural processes, from the functioning of animal organs to the cycling of global carbon. Yet, the study of microbial ecology is often limited by challenges in visualizing microbial processes and replicating the environmental conditions under which they unfold. Microfluidics operates at the characteristic scale at which microorganisms live and perform their functions, thus allowing for the observation and quantification of behaviors such as growth, motility, and responses to external cues, often with greater detail than classical techniques. By enabling a high degree of control in space and time of environmental conditions such as nutrient gradients, pH levels, and fluid flow patterns, microfluidics further provides the opportunity to study microbial processes in conditions that mimic the natural settings harboring microbial life. In this review, we describe how recent applications of microfluidic systems to microbial ecology have enriched our understanding of microbial life and microbial communities. We highlight discoveries enabled by microfluidic approaches ranging from single-cell behaviors to the functioning of multi-cellular communities, and we indicate potential future opportunities to use microfluidics to further advance our understanding of microbial processes and their implications.

Independent component analysis reveals 49 independently modulated gene sets within the global transcriptional regulatory architecture of multidrug-resistant Acinetobacter baumannii

Acinetobacter baumannii causes severe infections in humans, resists multiple antibiotics, and survives in stressful environmental conditions due to modulations of its complex transcriptional regulatory network (TRN). Unfortunately, our global understanding of the TRN in this emerging opportunistic pathogen is limited. Here, we apply independent component analysis, an unsupervised machine learning method, to a compendium of 139 RNA-seq data sets of three multidrug-resistant A. baumannii international clonal complex I strains (AB5075, AYE, and AB0057). This analysis allows us to define 49 independently modulated gene sets, which we call iModulons. Analysis of the identified A. baumannii iModulons reveals validating parallels to previously defined biological operons/regulons and provides a framework for defining unknown regulons. By utilizing the iModulons, we uncover potential mechanisms for a RpoS-independent general stress response, define global stress-virulence trade-offs, and identify conditions that may induce plasmid-borne multidrug resistance. The iModulons provide a model of the TRN that emphasizes the importance of transcriptional regulation of virulence phenotypes in A. baumannii. Furthermore, they suggest the possibility of future interventions to guide gene expression toward diminished pathogenic potential.IMPORTANCEThe rise in hospital outbreaks of multidrug-resistant Acinetobacter baumannii infections underscores the urgent need for alternatives to traditional broad-spectrum antibiotic therapies. The success of A. baumannii as a significant nosocomial pathogen is largely attributed to its ability to resist antibiotics and survive environmental stressors. However, there is limited literature available on the global, complex regulatory circuitry that shapes these phenotypes. Computational tools that can assist in the elucidation of A. baumannii's transcriptional regulatory network architecture can provide much-needed context for a comprehensive understanding of pathogenesis and virulence, as well as for the development of targeted therapies that modulate these pathways.

Extraction Methods Determine the Quality of Soil Microbiota Acquisition

The soil microbiome plays a key role in plant health. Native soil microbiome inoculation, metagenomic profiling, and high-throughput cultivation require efficient microbe extraction. Sonication and oscillation are the most common methods used to extract soil microbiomes. However, the extraction efficiency of these methods has not been investigated in full. In this study, we compared the culturable microbe numbers, community structures, and alpha diversities among the different methods, including sonication, oscillation, and centrifugation, and their processing times. The study results showed that sonication significantly increases the culturable colony number compared with oscillation and centrifugation. Furthermore, the sonication strategy was found to be the main factor influencing extraction efficiency, but increased sonication time can aid in recovery from this impact. Finally, the extraction processing times were found to have a significant negative relationship with α-diversity among the extracted microbiota. In conclusion, sonication is the main factor for enriching in situ microbiota, and increased extraction time significantly decreases the α-diversity of the extracted microbiota. The results of this study provide insights into the isolation and utilization of different microorganism sources.

Quantifying microbial robustness in dynamic environments using microfluidic single-cell cultivation

BACKGROUND

Microorganisms must respond to changes in their environment. Analysing the robustness of functions (i.e. performance stability) to such dynamic perturbations is of great interest in both laboratory and industrial settings. Recently, a quantification method capable of assessing the robustness of various functions, such as specific growth rate or product yield, across different conditions, time frames, and populations has been developed for microorganisms grown in a 96-well plate. In micro-titer-plates, environmental change is slow and undefined. Dynamic microfluidic single-cell cultivation (dMSCC) enables the precise maintenance and manipulation of microenvironments, while tracking single cells over time using live-cell imaging. Here, we combined dMSCC and a robustness quantification method to a pipeline for assessing performance stability to changes occurring within seconds or minutes.

RESULTS

Saccharomyces cerevisiae CEN.PK113-7D, harbouring a biosensor for intracellular ATP levels, was exposed to glucose feast-starvation cycles, with each condition lasting from 1.5 to 48 min over a 20 h period. A semi-automated image and data analysis pipeline was developed and applied to assess the performance and robustness of various functions at population, subpopulation, and single-cell resolution. We observed a decrease in specific growth rate but an increase in intracellular ATP levels with longer oscillation intervals. Cells subjected to 48 min oscillations exhibited the highest average ATP content, but the lowest stability over time and the highest heterogeneity within the population.

CONCLUSION

The proposed pipeline enabled the investigation of function stability in dynamic environments, both over time and within populations. The strategy allows for parallelisation and automation, and is easily adaptable to new organisms, biosensors, cultivation conditions, and oscillation frequencies. Insights on the microbial response to changing environments will guide strain development and bioprocess optimisation.

Structured community transitions explain the switching capacity of microbial systems

Microbial systems appear to exhibit a relatively high switching capacity of moving back and forth among few dominant communities (taxon memberships). While this switching behavior has been mainly attributed to random environmental factors, it remains unclear the extent to which internal community dynamics affect the switching capacity of microbial systems. Here, we integrate ecological theory and empirical data to demonstrate that structured community transitions increase the dependency of future communities on the current taxon membership, enhancing the switching capacity of microbial systems. Following a structuralist approach, we propose that each community is feasible within a unique domain in environmental parameter space. Then, structured transitions between any two communities can happen with probability proportional to the size of their feasibility domains and inversely proportional to their distance in environmental parameter space-which can be treated as a special case of the gravity model. We detect two broad classes of systems with structured transitions: one class where switching capacity is high across a wide range of community sizes and another class where switching capacity is high only inside a narrow size range. We corroborate our theory using temporal data of gut and oral microbiota (belonging to class 1) as well as vaginal and ocean microbiota (belonging to class 2). These results reveal that the topology of feasibility domains in environmental parameter space is a relevant property to understand the changing behavior of microbial systems. This knowledge can be potentially used to understand the relevant community size at which internal dynamics can be operating in microbial systems.

Horizontal gene transfer is predicted to overcome the diversity limit of competing microbial species

Natural microbial ecosystems harbor substantial diversity of competing species. Explaining such diversity is challenging, because in classic theories it is extremely infeasible for a large community of competing species to stably coexist in homogeneous environments. One important aspect mostly overlooked in these theories, however, is that microbes commonly share genetic materials with their neighbors through horizontal gene transfer (HGT), which enables the dynamic change of species growth rates due to the fitness effects of the mobile genetic elements (MGEs). Here, we establish a framework of species competition by accounting for the dynamic gene flow among competing microbes. Combining theoretical derivation and numerical simulations, we show that in many conditions HGT can surprisingly overcome the biodiversity limit predicted by the classic model and allow the coexistence of many competitors, by enabling dynamic neutrality of competing species. In contrast with the static neutrality proposed by previous theories, the diversity maintained by HGT is highly stable against random perturbations of microbial fitness. Our work highlights the importance of considering gene flow when addressing fundamental ecological questions in the world of microbes and has broad implications for the design and engineering of complex microbial consortia.

Exploring Genomics and Microbial Ecology: Analysis of Bidens pilosa L. Genetic Structure and Soil Microbiome Diversity by RAD-Seq and Metabarcoding

Bidens pilosa L., native to South America and commonly used for medicinal purposes, has been understudied at molecular and genomic levels and in its relationship with soil microorganisms. In this study, restriction site-associated DNA markers (RADseq) techniques were implemented to analyze genetic diversity and population structure, and metabarcoding to examine microbial composition in soils from Palmira, Sibundoy, and Bogotá, Colombia. A total of 2,984,123 loci and 3485 single nucleotide polymorphisms (SNPs) were identified, revealing a genetic variation of 12% between populations and 88% within individuals, and distributing the population into three main genetic groups, FST = 0.115 (p < 0.001) and FIT = 0.013 (p > 0.05). In the soil analysis, significant correlations were found between effective cation exchange capacity (ECEC) and apparent density, soil texture, and levels of Mg and Fe, as well as negative correlations between ECEC and Mg, and Mg, Fe, and Ca. Proteobacteria and Ascomycota emerged as the predominant bacterial and fungal phyla, respectively. Analyses of alpha, beta, and multifactorial diversity highlight the influence of ecological and environmental factors on these microbial communities, revealing specific patterns of clustering and association between bacteria and fungi in the studied locations.

A genus in the bacterial phylum Aquificota appears to be endemic to Aotearoa-New Zealand

Allopatric speciation has been difficult to examine among microorganisms, with prior reports of endemism restricted to sub-genus level taxa. Previous microbial community analysis via 16S rRNA gene sequencing of 925 geothermal springs from the Taupō Volcanic Zone (TVZ), Aotearoa-New Zealand, revealed widespread distribution and abundance of a single bacterial genus across 686 of these ecosystems (pH 1.2-9.6 and 17.4-99.8 °C). Here, we present evidence to suggest that this genus, Venenivibrio (phylum Aquificota), is endemic to Aotearoa-New Zealand. A specific environmental niche that increases habitat isolation was identified, with maximal read abundance of Venenivibrio occurring at pH 4-6, 50-70 °C, and low oxidation-reduction potentials. This was further highlighted by genomic and culture-based analyses of the only characterised species for the genus, Venenivibrio stagnispumantis CP.B2T, which confirmed a chemolithoautotrophic metabolism dependent on hydrogen oxidation. While similarity between Venenivibrio populations illustrated that dispersal is not limited across the TVZ, extensive amplicon, metagenomic, and phylogenomic analyses of global microbial communities from DNA sequence databases indicates Venenivibrio is geographically restricted to the Aotearoa-New Zealand archipelago. We conclude that geographic isolation, complemented by physicochemical constraints, has resulted in the establishment of an endemic bacterial genus.

A heritable iron memory enables decision-making in Escherichia coli

The importance of memory in bacterial decision-making is relatively unexplored. We show here that a prior experience of swarming is remembered when Escherichia coli encounters a new surface, improving its future swarming efficiency. We conducted >10,000 single-cell swarm assays to discover that cells store memory in the form of cellular iron levels. This "iron" memory preexists in planktonic cells, but the act of swarming reinforces it. A cell with low iron initiates swarming early and is a better swarmer, while the opposite is true for a cell with high iron. The swarming potential of a mother cell, which tracks with its iron memory, is passed down to its fourth-generation daughter cells. This memory is naturally lost by the seventh generation, but artificially manipulating iron levels allows it to persist much longer. A mathematical model with a time-delay component faithfully recreates the observed dynamic interconversions between different swarming potentials. We demonstrate that cellular iron levels also track with biofilm formation and antibiotic tolerance, suggesting that iron memory may impact other physiologies.

Minorities drive growth resumption in cross-feeding microbial communities

Microbial communities are fundamental to life on Earth. Different strains within these communities are often connected by a highly connected metabolic network, where the growth of one strain depends on the metabolic activities of other community members. While distributed metabolic functions allow microbes to reduce costs and optimize metabolic pathways, they make them metabolically dependent. Here, we hypothesize that such dependencies can be detrimental in situations where the external conditions change rapidly, as they often do in natural environments. After a shift in external conditions, microbes need to remodel their metabolism, but they can only resume growth once partners on which they depend have also adapted to the new conditions. It is currently not well understood how microbial communities resolve this dilemma and how metabolic interactions are reestablished after an environmental shift. To address this question, we investigated the dynamical responses to environmental perturbation by microbial consortia with distributed anabolic functions. By measuring the regrowth times at the single-cell level in spatially structured communities, we found that metabolic dependencies lead to a growth delay after an environmental shift. However, a minority of cells-those in the immediate neighborhood of their metabolic partners-can regrow quickly and come to numerically dominate the community after the shift. The spatial arrangement of a microbial community is thus a key factor in determining the communities' ability to maintain metabolic interactions and growth in fluctuating conditions. Our results suggest that environmental fluctuations can limit the emergence of metabolic dependencies between microorganisms.

Coupled environmental and demographic fluctuations shape the evolution of cooperative antimicrobial resistance

There is a pressing need to better understand how microbial populations respond to antimicrobial drugs, and to find mechanisms to possibly eradicate antimicrobial-resistant cells. The inactivation of antimicrobials by resistant microbes can often be viewed as a cooperative behaviour leading to the coexistence of resistant and sensitive cells in large populations and static environments. This picture is, however, greatly altered by the fluctuations arising in volatile environments, in which microbial communities commonly evolve. Here, we study the eco-evolutionary dynamics of a population consisting of an antimicrobial-resistant strain and microbes sensitive to antimicrobial drugs in a time-fluctuating environment, modelled by a carrying capacity randomly switching between states of abundance and scarcity. We assume that antimicrobial resistance (AMR) is a shared public good when the number of resistant cells exceeds a certain threshold. Eco-evolutionary dynamics is thus characterised by demographic noise (birth and death events) coupled to environmental fluctuations which can cause population bottlenecks. By combining analytical and computational means, we determine the environmental conditions for the long-lived coexistence and fixation of both strains, and characterise a fluctuation-driven AMR eradication mechanism, where resistant microbes experience bottlenecks leading to extinction. We also discuss the possible applications of our findings to laboratory-controlled experiments.

Fungal organic acid uptake of mineral-derived K is dependent on distance from carbon hotspot

IMPORTANCE

Fungal species are foundational members of soil ecosystems with vital contributions that support interspecies resource translocation. The minute details of these biogeochemical processes are poorly investigated. Here, we addressed this knowledge gap by probing fungal growth in a novel mineral-doped soil micromodel platform using spatially-resolved imaging methodologies. We found that fungi uptake K from K-rich minerals using organic acids exuded in a distance-dependent manner from a carbon-rich hotspot. While identification of specific mechanisms within soil remains challenging, our findings demonstrate the significance of reduced complexity platforms such as the mineral-doped micromodel in probing biogeochemical processes. These findings provide visualization into hyphal uptake and transport of mineral-derived nutrients in a resource-limited environment.

Insights into bacterial community metatranscriptome and metabolome in river water influenced by palm oil mill effluent final discharge

AIMS

This study aimed to investigate the effect of palm oil mill effluent (POME) final discharge on the active bacterial composition, gene expression, and metabolite profiles in the receiving rivers to establish a foundation for identifying potential biomarkers for monitoring POME pollution in rivers.

METHODS AND RESULTS

The POME final discharge, upstream (unpolluted by POME), and downstream (effluent receiving point) parts of the rivers from two sites were physicochemically characterized. The taxonomic and gene profiles were then evaluated using de novo metatranscriptomics, while the metabolites were detected using qualitative metabolomics. A similar bacterial community structure in the POME final discharge samples from both sites was recorded, but their composition varied. Redundancy analysis showed that several families, particularly Comamonadaceae and Burkholderiaceae [Pr(>F) = 0.028], were positively correlated with biochemical oxygen demand (BOD5) and chemical oxygen demand (COD). The results also showed significant enrichment of genes regulating various metabolisms in the POME-receiving rivers, with methane, carbon fixation pathway, and amino acids among the predominant metabolisms identified (FDR < 0.05, PostFC > 4, and PPDE > 0.95). This was further validated through qualitative metabolomics, whereby amino acids were detected as the predominant metabolites.

CONCLUSIONS

The results suggest that genes regulating amino acid metabolism have significant potential for developing effective biomonitoring and bioremediation strategies in river water influenced by POME final discharge, fostering a sustainable palm oil industry.

Fitness cost associated with cell phenotypic switching drives population diversification dynamics and controllability

Isogenic cell populations can cope with stress conditions by switching to alternative phenotypes. Even if it can lead to increased fitness in a natural context, this feature is typically unwanted for a range of applications (e.g., bioproduction, synthetic biology, and biomedicine) where it tends to make cellular response unpredictable. However, little is known about the diversification profiles that can be adopted by a cell population. Here, we characterize the diversification dynamics for various systems (bacteria and yeast) and for different phenotypes (utilization of alternative carbon sources, general stress response and more complex development patterns). Our results suggest that the diversification dynamics and the fitness cost associated with cell switching are coupled. To quantify the contribution of the switching cost on population dynamics, we design a stochastic model that let us reproduce the dynamics observed experimentally and identify three diversification regimes, i.e., constrained (at low switching cost), dispersed (at medium and high switching cost), and bursty (for very high switching cost). Furthermore, we use a cell-machine interface called Segregostat to demonstrate that different levels of control can be applied to these diversification regimes, enabling applications involving more precise cellular responses.

Advances in automated and reactive flow cytometry for synthetic biotechnology

Automated flow cytometry (FC) has been initially considered for bioprocess monitoring and optimization. More recently, new physical and software interfaces have been made available, facilitating the access to this technology for labs and industries. It also comes with new capabilities, such as being able to act on the cultivation conditions based on population data. This approach, known as reactive FC, extended the range of applications of automated FC to bioprocess control and the stabilization of cocultures, but also to the broad field of synthetic and systems biology for the characterization of gene circuits. However, several issues must be addressed before automated and reactive FC can be considered standard and modular technologies.

Growth phase estimation for abundant bacterial populations sampled longitudinally from human stool metagenomes

Longitudinal sampling of the stool has yielded important insights into the ecological dynamics of the human gut microbiome. However, human stool samples are available approximately once per day, while commensal population doubling times are likely on the order of minutes-to-hours. Despite this mismatch in timescales, much of the prior work on human gut microbiome time series modeling has assumed that day-to-day fluctuations in taxon abundances are related to population growth or death rates, which is likely not the case. Here, we propose an alternative model of the human gut as a stationary system, where population dynamics occur internally and the bacterial population sizes measured in a bolus of stool represent a steady-state endpoint of these dynamics. We formalize this idea as stochastic logistic growth. We show how this model provides a path toward estimating the growth phases of gut bacterial populations in situ. We validate our model predictions using an in vitro Escherichia coli growth experiment. Finally, we show how this method can be applied to densely-sampled human stool metagenomic time series data. We discuss how these growth phase estimates may be used to better inform metabolic modeling in flow-through ecosystems, like animal guts or industrial bioreactors.

Environmental, mechanistic and evolutionary landscape of antibiotic persistence

Recalcitrant infections pose a serious challenge by prolonging antibiotic therapies and contributing to the spread of antibiotic resistance, thereby threatening the successful treatment of bacterial infections. One potential contributing factor in persistent infections is antibiotic persistence, which involves the survival of transiently tolerant subpopulations of bacteria. This review summarizes the current understanding of antibiotic persistence, including its clinical significance and the environmental and evolutionary factors at play. Additionally, we discuss the emerging concept of persister regrowth and potential strategies to combat persister cells. Recent advances highlight the multifaceted nature of persistence, which is controlled by deterministic and stochastic elements and shaped by genetic and environmental factors. To translate in vitro findings to in vivo settings, it is crucial to include the heterogeneity and complexity of bacterial populations in natural environments. As researchers continue to gain a more holistic understanding of this phenomenon and develop effective treatments for persistent bacterial infections, the study of antibiotic persistence is likely to become increasingly complex.

Microbial Growth under Limiting Conditions-Future Perspectives

Microorganisms rule the functioning of our planet and each one of the individual macroscopic living creature. Nevertheless, microbial activity and growth status have always been challenging tasks to determine both in situ and in vivo. Microbial activity is generally related to growth, and the growth rate is a result of the availability of nutrients under adequate or adverse conditions faced by microbial cells in a changing environment. Most studies on microorganisms have been carried out under optimum or near-optimum growth conditions, but scarce information is available about microorganisms at slow-growing states (i.e., near-zero growth and maintenance metabolism). This study aims to better understand microorganisms under growth-limiting conditions. This is expected to provide new perspectives on the functions and relevance of the microbial world. This is because (i) microorganisms in nature frequently face conditions of severe growth limitation, (ii) microorganisms activate singular pathways (mostly genes remaining to be functionally annotated), resulting in a broad range of secondary metabolites, and (iii) the response of microorganisms to slow-growth conditions remains to be understood, including persistence strategies, gene expression, and cell differentiation both within clonal populations and due to the complexity of the environment.

Iron Memory in E. coli

The importance of memory in bacterial decision-making is relatively unexplored. We show here that a prior experience of swarming is remembered when E. coli encounters a new surface, improving its future swarming efficiency. We conducted >10,000 single-cell swarm assays to discover that cells store memory in the form of cellular iron levels. This memory pre-exists in planktonic cells, but the act of swarming reinforces it. A cell with low iron initiates swarming early and is a better swarmer, while the opposite is true for a cell with high iron. The swarming potential of a mother cell, whether low or high, is passed down to its fourth-generation daughter cells. This memory is naturally lost by the seventh generation, but artificially manipulating iron levels allows it to persist much longer. A mathematical model with a time-delay component faithfully recreates the observed dynamic interconversions between different swarming potentials. We also demonstrate that iron memory can integrate multiple stimuli, impacting other bacterial behaviors such as biofilm formation and antibiotic tolerance.

Microplastic biodegradability dependent responses of plastisphere antibiotic resistance to simulated freshwater-seawater shift in onshore marine aquaculture zones

MPs carrying ARGs can travel between freshwater and seawater due to intensive land-sea interaction in onshore marine aquaculture zones (OMAZ). However, the response of ARGs in plastisphere with different biodegradability to freshwater-seawater shift is still unknown. In this study, ARG dynamics and associated microbiota on biodegradable poly (butyleneadipate-co-terephthalate) (PBAT) and non-biodegradable polyethylene terephthalate (PET) MPs were investigated through a simulated freshwater-seawater shift. The results exhibited that freshwater-seawater shift significantly influenced ARG abundance in plastisphere. The relative abundance of most studied ARGs decreased rapidly in plastisphere after they entered seawater from freshwater but increased on PBAT after MPs entered freshwater from seawater. Besides, the high relative abundance of multi-drug resistance (MDR) genes occurred in plastisphere, and the co-change between most ARGs and mobile genetic elements indicated the role of horizontal gene transfer on ARG regulation. Proteobacteria was dominant phylum in plastisphere and the dominant genera, such as Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium, Afipia, Gemmobacter and Enhydrobacter, were significantly associated with qnrS, tet and MDR genes in plastisphere. Moreover, after MPs entered new water environment, the ARGs and microbiota genera in plastisphere changed significantly and tended to converge with those in receiving water. These results indicated that MP biodegradability and freshwater-seawater interaction influenced potential hosts and distributions of ARGs, of which biodegradable PBAT posed a high risk in ARG dissemination. This study would be helpful for understanding the impact of biodegradable MP pollution on spread of antibiotic resistance in OMAZ.

Interconnected versus unconnected microorganisms: Does it matter in anaerobic digestion functioning

Microorganisms in anaerobic digestion (AD) are essential for wastes/pollutants treatment and energy recovery. Due to microbial enormous diversity, developing effective perspectives to understand microbial roles therein is urgent. This study conducted AD of swine manure, used an ensemble-based network analysis to distinguish interconnected, unconnected, copresence (positively interconnected) and mutual-exclusion (negatively interconnected) microorganisms within microbial communities, and explored their importance towards AD performances, using amplicon sequencing of 16S rRNA and 16S rRNA gene. Our analyses revealed greater importance of interconnected than unconnected microorganisms towards CH₄ production and AD multifunctionality, which was attributed to higher niche breadth, deterministic community assembly, community stability and phylogenetic conservatism. The diversity was higher in unconnected than interconnected microorganisms, but was not linked to AD performances. Compared to copresence microorganisms, mutual-exclusion microorganisms showed greater and equal importance towards CH₄ production and AD multifunctionality, which was attributed to their roles in stabilizing microbial communities. The increased feedstock biodegradability, by replacing part of manure with fructose or apple waste, hardly affected the relative importance of interconnected versus unconnected microorganisms towards CH₄ production or AD multifunctionality. Our findings develop a new framework to understand microbial roles, and have important implications in targeted manipulation of critical microorganisms in waste-treatment systems.

Temporal dynamics of geothermal microbial communities in Aotearoa-New Zealand

Microbial biogeography studies, in particular for geothermal-associated habitats, have focused on spatial patterns and/or individual sites, which have limited ability to describe the dynamics of ecosystem behaviour. Here, we report the first comprehensive temporal study of bacterial and archaeal communities from an extensive range of geothermal features in Aotearoa-New Zealand. One hundred and fifteen water column samples from 31 geothermal ecosystems were taken over a 34-month period to ascertain microbial community stability (control sites), community response to both natural and anthropogenic disturbances in the local environment (disturbed sites) and temporal variation in spring diversity across different pH values (pH 3, 5, 7, 9) all at a similar temperature of 60–70°C (pH sites). Identical methodologies were employed to measure microbial diversity via 16S rRNA gene amplicon sequencing, along with 44 physicochemical parameters from each feature, to ensure confidence in comparing samples across timeframes. Our results indicated temperature and associated groundwater physicochemistry were the most likely parameters to vary stochastically in these geothermal features, with community abundances rather than composition more readily affected by a changing environment. However, variation in pH (pH ±1) had a more significant effect on community structure than temperature (±20°C), with alpha diversity failing to adequately measure temporal microbial disparity in geothermal features outside of circumneutral conditions. While a substantial physicochemical disturbance was required to shift community structures at the phylum level, geothermal ecosystems were resilient at this broad taxonomic rank and returned to a pre-disturbed state if environmental conditions re-established. These findings highlight the diverse controls between different microbial communities within the same habitat-type, expanding our understanding of temporal dynamics in extreme ecosystems.