Differential effects of pectin-based dietary fibre type and gut microbiota composition on in vitro fermentation outcomes.

Interactions between human gut microbiota and dietary fibres (DF) are influenced by the complexity and diversity of both individual microbiota and sources of DF. Based on 480 in vitro fermentations, a full factorial experiment was performed with six faecal inocula representing two enterotypes and three DF sources with nanometer, micrometer, and millimeter length-scales (apple pectin, apple cell walls and apple particles) at two concentrations. Increasing DF size reduced substrate disappearance and fermentation rates but not biomass growth. Concentrated DF enhanced butyrate production and lactate cross-feeding. Enterotype differentiated final microbial compositions but not biomass or fermentation metabolite profiles. Individual donor microbiota differences did not influence DF type or concentration effects but were manifested in the promotion of different functional microbes within each population with the capacity to degrade the DF substrates. Overall, consistent effects (independent of donor microbiota variation) of DF type and concentration on kinetics of substrate degradation, microbial biomass production, gas kinetics and metabolite profiles were found, which can form the basis for informed design of DF for desired rates/sites and consequences of gut fermentation. These results add further evidence to the concept that, despite variations between individuals, the human gut microbiota represents a community with conserved emergent properties.

Engineering natural microbiomes toward enhanced bioremediation by microbiome modeling.

Engineering natural microbiomes for biotechnological applications remains challenging, as metabolic interactions within microbiomes are largely unknown, and practical principles and tools for microbiome engineering are still lacking. Here, we present a combinatory top-down and bottom-up framework to engineer natural microbiomes for the construction of function-enhanced synthetic microbiomes. We show that application of herbicide and herbicide-degrader inoculation drives a convergent succession of different natural microbiomes toward functional microbiomes (e.g., enhanced bioremediation of herbicide-contaminated soils). We develop a metabolic modeling pipeline, SuperCC, that can be used to document metabolic interactions within microbiomes and to simulate the performances of different microbiomes. Using SuperCC, we construct bioremediation-enhanced synthetic microbiomes based on 18 keystone species identified from natural microbiomes. Our results highlight the importance of metabolic interactions in shaping microbiome functions and provide practical guidance for engineering natural microbiomes.

A combination of microbial electrolysis cells and bioaugmentation can effectively treat synthetic wastewater containing polycyclic aromatic hydrocarbon.

The anaerobic biodegradation of polycyclic aromatic hydrocarbons (PAHs) is challenging due to its toxic effect on the microbes. Microbial electrolysis cells (MECs), with their excellent characteristics of anodic and cathodic biofilms, can be a viable way to enhance the biodegradation of PAHs. This work assessed different cathode materials (carbon brush and nickel foam) combined with bioaugmentation on typical PAHs-naphthalene biodegradation and analyzed the inhibition amendment mechanism of microbial biofilms in MECs. Compared with the control, the degradation efficiency of naphthalene with the nickel foam cathode supplied with bioaugmentation dosage realized a maximum removal rate of 94.5 ± 3.2%. The highest daily recovered methane yield (227 ± 2 mL/gCOD) was also found in the nickel foam cathode supplied with bioaugmentation. Moreover, the microbial analysis demonstrated the significant switch of predominant PAH-degrading microorganisms from Pseudomonas in control to norank_f_Prolixibacteraceae in MECs. Furthermore, hydrogentrophic methanogenesis prevailed in MEC reactors, which is responsible for methane production. This study proved that MEC combined with bioaugmentation could effectively alleviate the inhibition of PAH, with the nickel foam cathode obtaining the fastest recovery rate in terms of methane yield.

Spatial profiles of the bacterial microbiota throughout the gastrointestinal tract of dairy goats.

The gastrointestinal tract (GIT) is stationed by a dynamic and complex microbial community with functions in digestion, metabolism, immunomodulation, and reproduction. However, there is relatively little research on the composition and function of microorganisms in different GIT segments in dairy goats. Herein, 80 chyme samples were taken from ten GIT sites of eight Xinong Saanen dairy goats and then analyzed and identified the microbial composition via 16S rRNA V1-V9 amplicon sequencing. A total of 6669 different operational taxonomic units (OTUs) were clustered, and 187 OTUs were shared by ten GIT segments. We observed 264 species belonging to 23 different phyla scattered across ten GITs, with Firmicutes (52.42%) and Bacteroidetes (22.88%) predominating. The results revealed obvious location differences in the composition, diversity, and function of the GIT microbiota. In LEfSe analysis, unidentified_Lachnospiraceae and unidentified_Succinniclassicum were significantly enriched in the four chambers of stomach, with functions in carbohydrate fermentation to compose short-chain fatty acids. Aeriscardovia, Candidatus_Saccharimonas, and Romboutsia were significantly higher in the foregut, playing an important role in synthesizing enzymes, amino acids, and vitamins and immunomodulation. Akkermansia, Bacteroides, and Alistipes were significantly abundant in the hindgut to degrade polysaccharides and oligosaccharides, etc. From rumen to rectum, α-diversity decreased first and then increased, while ß-diversity showed the opposite trend. Metabolism was the major function of the GIT microbiome predicted by PICRUSt2, but with variation in target substrates along the regions. In summary, GIT segments play a decisive role in the composition and functions of microorganisms. KEY POINTS: • The jejunum and ileum were harsh for microorganisms to colonize due to the presence of bile acids, enzymes, faster chyme circulation, etc., exhibiting the lowest α-diversity and the highest ß-diversity. • Variability in microbial profiles between the three foregut segments was greater than four chambers of stomach and hindgut, with a higher abundance of Firmicutes dominating than others. • Dairy goats dominated a higher abundance of Kiritimatiellaeota than cows, which was reported to be associated with fatty acid synthesis.

Combat phytopathogenic bacteria employing Argirium-SUNCs: limits and perspectives.

Bacterial plant diseases are difficult to control as the durability of deployed control measures is thwarted by continuous and rapid changing of bacterial populations. Although application of copper compounds to plants is the most widespread and inexpensive control measure, it is often partially efficacious for the frequent appearance of copper-resistant bacterial strains and it is raising concerns for the harmful effects of copper on environment and human health. Consequently, European Community included copper compounds in the list of substances candidates for substitution. Nanotechnologies and the application of nanoparticles seem to respond to the need to find new very effective and durable measures. We believe that Argirium-SUNCs®, silver ultra nanoclusters with an average size of 1.79 nm and characterized by rare oxidative states (Ag2+/3+), represent a valid candidate as a nano-bactericide in the control of plant bacterial diseases. Respect to the many silver nanoparticles described in the literature, Argirium-SUNCs have many strengths due to the reproducibility of the synthesis method, the purity and the stability of the preparation, the very strong (less than 1 ppm) antimicrobial, and anti-biofilm activities. In this mini-review, we provide information on this nanomaterial and on the possible application in agriculture. KEY POINTS: • Argirium-SUNCs have strong antimicrobial activities against phytopathogenic bacteria. • Argirium-SUNCs are a possible plant protection product. • Argirium-SUNCs protect tomato plants against bacterial speck disease.

Metagenomic and flavoromic profiling reveals the correlation between the microorganisms and volatile flavor compounds in Monascus-fermented cheese.

The Monascus-fermented cheese (MC) is a unique cheese product that undergoes multi-strain fermentation, imparting it with distinct flavor qualities. To clarify the role of microorganisms in the formation of flavor in MC, this study employed SPME (arrow)-GC-MS, GC-O integrated with PLS-DA to investigate variations in cheese flavors represented by volatile flavor compounds across 90-day ripening periods. Metagenomic datasets were utilized to identify taxonomic and functional changes in the microorganisms. The results showed a total of 26 characteristic flavor compounds in MC at different ripening periods (VIP＞1, p < 0.05), including butanoic acid, hexanoic acid, butanoic acid ethyl ester, hexanoic acid butyl ester, 2-heptanone and 2-octanone. According to NR database annotation, the genera Monascus, Lactococcus, Aspergillus, Lactiplantibacillus, Staphylococcus, Flavobacterium, Bacillus, Clostridium, Meyerozyma, and Enterobacter were closely associated with flavor formation in MC. Ester compounds were linked to Monascus, Meyerozyma, Staphylococcus, Lactiplantibacillus, and Bacillus. Acid compounds were linked to Lactococcus, Lactobacillus, Staphylococcus, and Bacillus. The production of methyl ketones was closely related to the genera Monascus, Staphylococcus, Lactiplantibacillus, Lactococcus, Bacillus, and Flavobacterium. This study offers insights into the microorganisms of MC and its contribution to flavor development, thereby enriching our understanding of this fascinating dairy product.

Deciphering the core microbes and their interactions in spontaneous Baijiu fermentation: A comprehensive review.

The spontaneous Baijiu fermentation system harbors a complex microbiome that is highly dynamic in time and space and varies depending on the Jiuqu starters and environmental factors. The intricate microbiota presents in the fermentation environment is responsible for carrying out various reactions. These reactions necessitate the interaction among the core microbes to influence the community function, ultimately shaping the distinct Baijiu styles through the process of spontaneous fermentation. Numerous studies have been conducted to enhance our understanding of the diversity, succession, and function of microbial communities with the aim of improving fermentation manipulation. However, a comprehensive and critical assessment of the core microbes and their interaction remains one of the significant challenges in the Baijiu fermentation industry. This paper focuses on the fermentation properties of core microbes. We discuss the state of the art of microbial traceability, highlighting the crucial role of environmental and starter microbiota in the Baijiu brewing microbiome. Also, we discuss the various interactions between microbes in the Baijiu production system and propose a potential conceptual framework that involves constructing predictive network models to simplify and quantify microbial interactions using co-culture models. This approach offers effective strategies for understanding the core microbes and their interactions, thus beneficial for the management of microbiota and the regulation of interactions in Baijiu fermentation processes.

Revealing microbiota characteristics and predicting flavor-producing sub-communities in Nongxiangxing baijiu pit mud through metagenomic analysis and metabolic modeling.

The microorganisms of the pit mud (PM) of Nongxiangxing baijiu (NXXB) have an important role in the synthesis of flavor substances, and they determine attributes and quality of baijiu. Herein, we utilize metagenomics and genome-scale metabolic models (GSMMs) to investigate the microbial composition, metabolic functions in PM microbiota, as well as to identify microorganisms and communities linked to flavor compounds. Metagenomic data revealed that the most prevalent assembly of bacteria and archaea was Proteiniphilum, Caproicibacterium, Petrimonas, Lactobacillus, Clostridium, Aminobacterium, Syntrophomonas, Methanobacterium, Methanoculleus, and Methanosarcina. The important enzymes ofPMwere in bothGH and GT familymetabolism. A total of 38 high-quality metagenome-assembled genomes (MAGs) were obtained, including those at the family level (n = 13), genus level (n = 17), and species level (n = 8). GSMMs of the 38 MAGs were then constructed. From the GSMMs, individual and community capabilities respectively were predicted to be able to produce 111 metabolites and 598 metabolites. Twenty-three predicted metabolites were consistent with the metabonomics detected flavors and served as targets. Twelve sub-community of were screened by cross-feeding of 38 GSMMs. Of them, Methanobacterium, Sphaerochaeta, Muricomes intestini, Methanobacteriaceae, Synergistaceae, and Caloramator were core microorganisms for targets in each sub-community. Overall, this study of metagenomic and target-community screening could help our understanding of the metabolite-microbiome association and further bioregulation of baijiu.

Natural variation of immune epitopes reveals intrabacterial antagonism.

Plants and animals detect biomolecules termed microbe-associated molecular patterns (MAMPs) and induce immunity. Agricultural production is severely impacted by pathogens which can be controlled by transferring immune receptors. However, most studies use a single MAMP epitope and the impact of diverse multicopy MAMPs on immune induction is unknown. Here, we characterized the epitope landscape from five proteinaceous MAMPs across 4,228 plant-associated bacterial genomes. Despite the diversity sampled, natural variation was constrained and experimentally testable. Immune perception in both Arabidopsis and tomato depended on both epitope sequence and copy number variation. For example, Elongation Factor Tu is predominantly single copy, and 92% of its epitopes are immunogenic. Conversely, 99.9% of bacterial genomes contain multiple cold shock proteins, and 46% carry a nonimmunogenic form. We uncovered a mechanism for immune evasion, intrabacterial antagonism, where a nonimmunogenic cold shock protein blocks perception of immunogenic forms encoded in the same genome. These data will lay the foundation for immune receptor deployment and engineering based on natural variation.

Application of machine learning for antibiotic resistance in water and wastewater: A systematic review.

Antibiotic resistance (AR) is considered one of the greatest global threats in the current century, which can only be overcome if all interconnected areas of humans, animals and the environment are taken into account as part of the One Health concept proposed by the World Health Organization (WHO). Water and wastewater are among the most important environmental media of AR sources, where the phenomena are generally non-linear. Therefore, the aim of this study was to investigate the application of machine learning-based methods (MLMs) to solve AR-induced problems in water and wastewater. For this purpose, most relevant databases were searched in the period between 1987 and 2023 to systematically analyze and categorize the applications. Accordingly, the results showed that out of 12 applications, 11 (91.6%) were for shallow learning and 1 (8.3%) for deep learning. In shallow learning category, n = 6, 50% of the applications were regression and n = 4, 33.3% were classification, mainly using artificial neural networks, decision trees and Bayesian methods for the following objectives: Predicting the survival of antibiotic-resistant bacteria (ARB), determining the order of influencing parameters on AR-based scores, and identifying the major sources of antibiotic resistance genes (ARGs). In addition, only one study (8.3%) was found for clustering and no study for association. Surprisingly, deep learning had been used in only one study (8.3%) to predict ARGs sequences. Therefore, working on the knowledge gaps of AR, especially using clustering, association and deep learning methods, would be a promising option to analyze more aspects of the related problems. However, there is still a long way to go to consider and apply MLMs as unique approaches to study different aspects of AR in water and wastewater.

Long-term chemical and organic fertilization induces distinct variations of microbial associations but unanimous elevation of soil multifunctionality.

Intricate microbial associations contribute greatly to the multiple functions (multifunctionality) of natural ecosystems. However, the relationship between microbial associations and soil multifunctionality (SMF) in artificial ecosystems, particularly in agricultural ecosystem with frequent fertilization, remains unclear. In this study, based on a 28-year paddy field experiment, high-throughput sequencing and networks analysis was performed to investigate changes in soil microbial (archaea, bacteria, fungi, and protists) associations and how these changes correlate with SMF under long-term fertilization. Compared to no fertilization (CK), both chemical fertilization with N, P, and K (CF) and chemical fertilization plus rice straw retention (CFR) treatments showed significantly higher soil nutrient content, grain yield, microbial abundance, and SMF. With the exception of archaeal diversity, the CF treatment exhibited the lowest bacterial, fungal, and protist diversity, and the simplest microbial co-occurrence network. In contrast, the CFR treatment had the lowest archaeal diversity, but the highest bacterial, fungal, and protist diversity. Moreover, the CFR treatment exhibited the most complex microbial co-occurrence network with the highest number of nodes, edges, and interkingdom edges. These results highlight that both chemical fertilization with and without straw retention caused high ecosystem multifunctionality while changing microbial association oppositely. Furthermore, these results indicate that rice straw retention contributes to the development of the soil microbiome and ensures the sustainability of high-level ecosystem multifunctionality.

Advancements in bacterial chemotaxis: Utilizing the navigational intelligence of bacteria and its practical applications.

The fascinating world of microscopic life unveils a captivating spectacle as bacteria effortlessly maneuver through their surroundings with astonishing accuracy, guided by the intricate mechanism of chemotaxis. This review explores the complex mechanisms behind this behavior, analyzing the flagellum as the driving force and unraveling the intricate signaling pathways that govern its movement. We delve into the hidden costs and benefits of this intricate skill, analyzing its potential to propagate antibiotic resistance gene while shedding light on its vital role in plant colonization and beneficial symbiosis. We explore the realm of human intervention, considering strategies to manipulate bacterial chemotaxis for various applications, including nutrient cycling, algal bloom and biofilm formation. This review explores the wide range of applications for bacterial capabilities, from targeted drug delivery in medicine to bioremediation and disease control in the environment. Ultimately, through unraveling the intricacies of bacterial movement, we can enhance our comprehension of the intricate web of life on our planet. This knowledge opens up avenues for progress in fields such as medicine, agriculture, and environmental conservation.

Exposure to environmental pollutants selects for xenobiotic-degrading functions in the human gut microbiome.

Environmental pollutants from different chemical families may reach the gut microbiome, where they can be metabolized and transformed. However, how our gut symbionts respond to the exposure to environmental pollution is still underexplored. In this observational, cohort study, we aim to investigate the influence of environmental pollution on the gut microbiome composition and potential activity by shotgun metagenomics. We select as a case study a population living in a highly polluted area in Campania region (Southern Italy), proposed as an ideal field for exposomic studies and we compare the fecal microbiome of 359 subjects living in areas with high, medium and low environmental pollution. We highlight changes in gut microbiome composition and functionality that were driven by pollution exposure. Subjects from highly polluted areas show higher blood concentrations of dioxin and heavy metals, as well as an increase in microbial genes related to degradation and/or resistance to these molecules. Here we demonstrate the dramatic effect that environmental xenobiotics have on gut microbial communities, shaping their composition and boosting the selection of strains with degrading capacity. The gut microbiome can be considered as a pivotal player in the environment-health interaction that may contribute to detoxifying toxic compounds and should be taken into account when developing risk assessment models. The study was registered at ClinicalTrials.gov with the identifier NCT05976126.

The link between ancient microbial fluoride resistance mechanisms and bioengineering organofluorine degradation or synthesis.

Fluorinated organic chemicals, such as per- and polyfluorinated alkyl substances (PFAS) and fluorinated pesticides, are both broadly useful and unusually long-lived. To combat problems related to the accumulation of these compounds, microbial PFAS and organofluorine degradation and biosynthesis of less-fluorinated replacement chemicals are under intense study. Both efforts are undermined by the substantial toxicity of fluoride, an anion that powerfully inhibits metabolism. Microorganisms have contended with environmental mineral fluoride over evolutionary time, evolving a suite of detoxification mechanisms. In this perspective, we synthesize emerging ideas on microbial defluorination/fluorination and fluoride resistance mechanisms and identify best approaches for bioengineering new approaches for degrading and making organofluorine compounds.

Evaluation of Automated Disk Diffusion Antimicrobial Susceptibility Testing Using Radian® In-Line Carousel.

Antimicrobial susceptibility testing (AST) by disk diffusion provides an accurate image of bacterial growth, enabling the detection of culture purity, heterogeneous growth, and antibiotic interactions. However, this manual method is time-consuming and visual interpretation is prone to errors. To overcome these disadvantages, the Radian® In-Line Carousel (Copan, Brescia, Italy) was launched, which is a WASPLab® module dedicated to full automation of (pre)-analytical steps as well as interpretation of disk diffusion AST. However, until now, no evaluation of Radian® against manual disk diffusion has been performed. We assessed the categorical agreement (CA) between standardized disk diffusion (reference method) and Radian® using EUCAST 2021 breakpoints. We tested 135 non-duplicate strains, selected from the National EUCAST challenge panel, clinical strains, and external quality controls. The strains included Enterobacterales (n = 63), Enterococcus faecalis (n = 3), Enterococcus faecium (n = 10), Pseudomonas aeruginosa (n = 16), Staphylococcus aureus (n = 19), coagulase-negative staphylococci (n = 4), and Streptococcus spp. (n = 20). Furthermore, we explored antibiotic disk thermolability in the WASP Radian® carousel by testing 10 ATCC® strains up to 7 days. The observed CA was 95.3%, 96.3%, 93.8%, 97.3% and 98.0% for Enterobacterales, Enterococcus spp., P. aeruginosa, Staphylococcus spp. and Streptococcus spp., respectively, resulting in an acceptable overall CA for all groups. (Very) major error rates were ≤ 5% for all antibiotics. Antibiotic disk thermostability was confirmed up to 4 days in the WASP Radian® In-Line Carousel. The Radian® In-Line Carousel provides a fully automated solution for accurate disk diffusion AST, reducing workload and improving standardization and traceability. In addition, our study demonstrated the thermostability of antibiotic disks up to 4 days in the WASP Radian® In-Line Carousel.

A strategy for differential abundance analysis of sparse microbiome data with group-wise structured zeros.

Comparing the abundance of microbial communities between different groups or obtained under different experimental conditions using count sequence data is a challenging task due to various issues such as inflated zero counts, overdispersion, and non-normality. Several methods and procedures based on counts, their transformation and compositionality have been proposed in the literature to detect differentially abundant species in datasets containing hundreds to thousands of microbial species. Despite efforts to address the large numbers of zeros present in microbiome datasets, even after careful data preprocessing, the performance of existing methods is impaired by the presence of inflated zero counts and group-wise structured zeros (i.e. all zero counts in a group). We propose and validate using extensive simulations an approach combining two differential abundance testing methods, namely DESeq2-ZINBWaVE and DESeq2, to address the issues of zero-inflation and group-wise structured zeros, respectively. This combined approach was subsequently successfully applied to two plant microbiome datasets that revealed a number of taxa as interesting candidates for further experimental validation.

Assessing the efficiency and microbial diversity of H2S-removing biotrickling filters at various pH conditions.

This study aimed to investigate the operation of three parallel biotrickling filters (BTFs) in removing H2S at different pH conditions (haloalkaliphilic, neutrophilic, and acidophilic) and their associated microbial population in the biodesulfurization process. BTF columns were inoculated with enriched inoculum and experiments were performed by gradually reducing Empty Bed Retention Time (EBRT) and increasing inlet concentration in which the maximum removal efficiency and maximum elimination capacity in EBRT 60 s reached their maximum level in haloalkaline condition (91% and 179.5 g S-H2S m-3 h-1). For visualizing the attached microbial biofilms on pall rings, Scanning Electron Microscopy (SEM) was used and microbial community structure analysis by NGS showed that the most abundant phyla in haBTF, nBTF, and aBTF belong to Gammaproteobacteria, Betaproteobacteria, and Acidithiobacillia, respectively. Shannon and Simpson indexes evaluation showed a lower diversity of bacteria in the aBTF reactor than that of nBTF and haBTF and beta analysis indicated a different composition of bacteria in haBTF compared to the other two filters. These results indicated that the proper performance of BTF under haloalkaliphilic conditions is the most effective way for H2S removal from air pollutants of different industries.

Antimicrobials: An update on new strategies to diversify treatment for bacterial infections.

Ninety-five years after Fleming's discovery of penicillin, a bounty of antibiotic compounds have been discovered, modified, or synthesised. Diversification of target sites, improved stability and altered activity spectra have enabled continued antibiotic efficacy, but overwhelming reliance and misuse has fuelled the global spread of antimicrobial resistance (AMR). An estimated 1.27 million deaths were attributable to antibiotic resistant bacteria in 2019, representing a major threat to modern medicine. Although antibiotics remain at the heart of strategies for treatment and control of bacterial diseases, the threat of AMR has reached catastrophic proportions urgently calling for fresh innovation. The last decade has been peppered with ground-breaking developments in genome sequencing, high throughput screening technologies and machine learning. These advances have opened new doors for bioprospecting for novel antimicrobials. They have also enabled more thorough exploration of complex and polymicrobial infections and interactions with the healthy microbiome. Using models of infection that more closely resemble the infection state in vivo, we are now beginning to measure the impacts of antimicrobial therapy on host/microbiota/pathogen interactions. However new approaches are needed for developing and standardising appropriate methods to measure efficacy of novel antimicrobial combinations in these contexts. A battery of promising new antimicrobials is now in various stages of development including co-administered inhibitors, phages, nanoparticles, immunotherapy, anti-biofilm and anti-virulence agents. These novel therapeutics need multidisciplinary collaboration and new ways of thinking to bring them into large scale clinical use.

Microbial metabolites as modulators of host physiology.

The gut microbiota is increasingly recognised as a key player in influencing human health and changes in the gut microbiota have been strongly linked with many non-communicable conditions in humans such as type 2 diabetes, obesity and cardiovascular disease. However, characterising the molecular mechanisms that underpin these associations remains an important challenge for researchers. The gut microbiota is a complex microbial community that acts as a metabolic interface to transform ingested food (and other xenobiotics) into metabolites that are detected in the host faeces, urine and blood. Many of these metabolites are only produced by microbes and there is accumulating evidence to suggest that these microbe-specific metabolites do act as effectors to influence human physiology. For example, the gut microbiota can digest dietary complex polysaccharides (such as fibre) into short-chain fatty acids (SCFA) such as acetate, propionate and butyrate that have a pervasive role in host physiology from nutrition to immune function. In this review we will outline our current understanding of the role of some key microbial metabolites, such as SCFA, indole and bile acids, in human health. Whilst many studies linking microbial metabolites with human health are correlative we will try to highlight examples where genetic evidence is available to support a specific role for a microbial metabolite in host health and well-being.

New insights in bacterial organophosphorus cycling: From human pathogens to environmental bacteria.

In terrestrial and aquatic ecosystems, phosphorus (P) availability controls primary production, with consequences for climate regulation and global food security. Understanding the microbial controls on the global P cycle is a prerequisite for minimising our reliance on non-renewable phosphate rock reserves and reducing pollution associated with excessive P fertiliser use. This recognised importance has reinvigorated research into microbial P cycling, which was pioneered over 75 years ago through the study of human pathogenic bacteria-host interactions. Immobilised organic P represents a significant fraction of the total P pool. Hence, microbes have evolved a plethora of mechanisms to transform this fraction into labile inorganic phosphate, the building block for numerous biological molecules. The 'genomics era' has revealed an extraordinary diversity of organic P cycling genes exist in the environment and studies going 'back to the lab' are determining how this diversity relates to function. Through this integrated approach, many hitherto unknown genes and proteins that are involved in microbial P cycling have been discovered. Not only do these fundamental discoveries push the frontier of our knowledge, but several examples also provide exciting opportunities for biotechnology and present possible solutions for improving the sustainability of how we grow our food, both locally and globally. In this review, we provide a comprehensive overview of bacterial organic P cycling, covering studies on human pathogens and how this knowledge is informing new discoveries in environmental microbiology.