Selective whole-genome sequencing of Plasmodium parasites directly from blood samples by nanopore adaptive sampling

IMPORTANCE

Malaria is caused by parasites of the genus Plasmodium, and reached a global disease burden of 247 million cases in 2021. To study drug resistance mutations and parasite population dynamics, whole-genome sequencing of patient blood samples is commonly performed. However, the predominance of human DNA in these samples imposes the need for time-consuming laboratory procedures to enrich Plasmodium DNA. We used the Oxford Nanopore Technologies' adaptive sampling feature to circumvent this problem and enrich Plasmodium reads directly during the sequencing run. We demonstrate that adaptive nanopore sequencing efficiently enriches Plasmodium reads, which simplifies and shortens the timeline from blood collection to parasite sequencing. In addition, we show that the obtained data can be used for monitoring genetic markers, or to generate nearly complete genomes. Finally, owing to its inherent mobility, this technology can be easily applied on-site in endemic areas where patients would benefit the most from genomic surveillance.

Human Milk Bioactive Components and Child Growth and Body Composition in the First 2 Years: A Systematic Review

Human milk (HM) contains macronutrients, micronutrients, and a multitude of other bioactive factors, which can have a long-term impact on infant growth and development. We systematically searched MEDLINE, EMBASE, Cochrane Library, Scopus, and Web of Science to synthesize evidence published between 1980 and 2022 on HM components and anthropometry through 2 y of age among term-born infants. From 9992 abstracts screened, 141 articles were included and categorized based on their reporting of HM micronutrients, macronutrients, or bioactive components. Bioactives including hormones, HM oligosaccharides (HMOs), and immunomodulatory components are reported here, based on 75 articles from 69 unique studies reporting observations from 9980 dyads. Research designs, milk collection strategies, sampling times, geographic and socioeconomic settings, reporting practices, and outcomes varied considerably. Meta-analyses were not possible because data collection times and reporting were inconsistent among the studies included. Few measured infant HM intake, adjusted for confounders, precisely captured breastfeeding exclusivity, or adequately described HM collection protocols. Only 5 studies (6%) had high overall quality scores. Hormones were the most extensively examined bioactive with 46 articles (n = 6773 dyads), compared with 13 (n = 2640 dyads) for HMOs and 12 (n = 1422 dyads) for immunomodulatory components. Two studies conducted untargeted metabolomics. Leptin and adiponectin demonstrated inverse associations with infant growth, although several studies found no associations. No consistent associations were found between individual HMOs and infant growth outcomes. Among immunomodulatory components in HM, IL-6 demonstrated inverse relationships with infant growth. Current research on HM bioactives is largely inconclusive and is insufficient to address the complex composition of HM. Future research should ideally capture HM intake, use biologically relevant anthropometrics, and integrate components across categories, embracing a systems biology approach to better understand how HM components work independently and synergistically to influence infant growth.

Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics

Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this library, or "suspects," were derived from unannotated spectra that could be linked in a molecular network to an annotated spectrum. Annotations were propagated to unknowns based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer's brain phenotype. The nearest neighbor suspect spectral library is openly available for download or for data analysis through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

Portosystemic shunt placement reveals blood signatures for the development of hepatic encephalopathy through mass spectrometry

Elective transjugular intrahepatic portosystemic shunt (TIPS) placement can worsen cognitive dysfunction in hepatic encephalopathy (HE) patients due to toxins, including possible microbial metabolites, entering the systemic circulation. We conducted untargeted metabolomics on a prospective cohort of 22 patients with cirrhosis undergoing elective TIPS placement and followed them up to one year post TIPS for HE development. Here we suggest that pre-existing intrahepatic shunting predicts HE severity post-TIPS. Bile acid levels decrease in the peripheral vein post-TIPS, and the abundances of three specific conjugated di- and tri-hydroxylated bile acids are inversely correlated with HE grade. Bilirubins and glycerophosphocholines undergo chemical modifications pre- to post-TIPS and based on HE grade. Our results suggest that TIPS-induced metabolome changes can impact HE development, and that pre-existing intrahepatic shunting could be used to predict HE severity post-TIPS.

Pre- and Post-Portosystemic Shunt Placement Metabolomics Reveal Molecular Signatures for the Development of Hepatic Encephalopathy

Hepatic encephalopathy (HE) is a common complication of advanced liver disease causing brain dysfunction. This is likely due to the accumulation of unfiltered toxins within the bloodstream. A known risk factor for developing or worsening HE is the placement of a transjugular intrahepatic portosystemic shunt (TIPS), which connects the pre-hepatic and post-hepatic circulation allowing some blood to bypass the dysfunctional liver and decreases portal hypertension. To better understand the pathophysiology of post-TIPS HE, we conducted a multi-center prospective cohort study employing metabolomic analyses on hepatic vein and peripheral vein blood samples from participants with cirrhosis undergoing elective TIPS placement, measuring chemical modifications and changes in concentrations of metabolites resulting from TIPS placement. In doing so, we identified numerous alterations in metabolites, including bile acids, glycerophosphocholines, and bilirubins possibly implicated in the development and severity of HE.

Enhancing untargeted metabolomics using metadata-based source annotation

Human untargeted metabolomics studies annotate only ~10% of molecular features. We introduce reference-data-driven analysis to match metabolomics tandem mass spectrometry (MS/MS) data against metadata-annotated source data as a pseudo-MS/MS reference library. Applying this approach to food source data, we show that it increases MS/MS spectral usage 5.1-fold over conventional structural MS/MS library matches and allows empirical assessment of dietary patterns from untargeted data.

An untargeted metabolomics analysis of exogenous chemicals in human milk and transfer to the infant

Human milk is the optimal infant nutrition. However, although human-derived metabolites (such as lipids and oligosaccharides) in human milk are regularly reported, the presence of exogenous chemicals (such as drugs, food, and synthetic compounds) are often not addressed. To understand the types of exogenous compounds that might be present, human milk (n = 996) was analyzed by untargeted metabolomics. This analysis revealed that lifestyle molecules, such as medications and their metabolites, and industrial sources, such as plasticizers, cosmetics, and other personal care products, are found in human milk. We provide further evidence that some of these lifestyle molecules are also detectable in the newborn's stool. Thus, this study gives important insight into the types of exposures infants receiving human milk might ingest due to the lifestyle choices, exposure, or medical status of the lactating parent.

Association between fetal abdominal growth trajectories, maternal metabolite signatures early in pregnancy, and childhood growth and adiposity: prospective observational multinational INTERBIO-21st fetal study

BACKGROUND

Obesity predominantly affects populations in high-income countries and those countries facing epidemiological transition. The risk of childhood obesity is increased among infants who had overweight or obesity at birth, but in low-resource settings one in five infants are born small for gestational age. We aimed to study the relationships between: (1) maternal metabolite signatures; (2) fetal abdominal growth; and (3) postnatal growth, adiposity, and neurodevelopment.

METHODS

In the prospective, multinational, observational INTERBIO-21st fetal study, conducted in maternity units in Pelotas (Brazil), Nairobi (Kenya), Karachi (Pakistan), Soweto (South Africa), Mae Sot (Thailand), and Oxford (UK), we enrolled women (≥18 years, with a BMI of less than 35 kg/m², natural conception, and a singleton pregnancy) who initiated antenatal care before 14 weeks' gestation. Ultrasound scans were performed every 5±1 weeks until delivery to measure fetal growth and feto-placental blood flow, and we used finite mixture models to derive growth trajectories of abdominal circumference. The infants' health, growth, and development were monitored from birth to age 2 years. Early pregnancy maternal blood and umbilical cord venous blood samples were collected for untargeted metabolomic analysis.

FINDINGS

From Feb 8, 2012, to Nov 30, 2019, we enrolled 3598 pregnant women and followed up their infants to 2 years of age. We identified four ultrasound-derived trajectories of fetal abdominal circumference growth that accelerated or decelerated within a crucial 20-25 week gestational age window: faltering growth, early accelerating growth, late accelerating growth, and median growth tracking. These distinct phenotypes had matching feto-placental blood flow patterns throughout pregnancy, and different growth, adiposity, vision, and neurodevelopment outcomes in early childhood. There were 709 maternal metabolites with positive effect for the faltering growth phenotype and 54 for the early accelerating growth phenotype; 31 maternal metabolites had a negative effect for the faltering growth phenotype and 76 for the early accelerating growth phenotype. Metabolites associated with the faltering growth phenotype had statistically significant odds ratios close to 1·5 (ie, suggesting upregulation of metabolic pathways of impaired fetal growth). The metabolites had a reciprocal relationship with the early accelerating growth phenotype, with statistically significant odds ratios close to 0.6 (ie, suggesting downregulation of fetal growth acceleration). The maternal metabolite signatures included 5-hydroxy-eicosatetraenoic acid, and 11 phosphatidylcholines linked to oxylipin or saturated fatty acid sidechains. The fungicide, chlorothalonil, was highly abundant in the early accelerating growth phenotype group.

INTERPRETATION

Early pregnancy lipid biology associated with fetal abdominal growth trajectories is an indicator of patterns of growth, adiposity, vision, and neurodevelopment up to the age of 2 years. Our findings could contribute to the earlier identification of infants at risk of obesity.

FUNDING

Bill & Melinda Gates Foundation.

Multiomic Analyses of Nascent Preterm Infant Microbiomes Differentiation Suggest Opportunities for Targeted Intervention

The first week after birth is a critical time for the establishment of microbial communities for infants. Preterm infants face unique environmental impacts on their newly acquired microbiomes, including increased incidence of cesarean section delivery and exposure to antibiotics as well as delayed enteral feeding and reduced human interaction during their intensive care unit stay. Using contextualized paired metabolomics and 16S sequencing data, the development of the gut, skin, and oral microbiomes of infants is profiled daily for the first week after birth, and it is found that the skin microbiome appears robust to early life perturbation, while direct exposure of infants to antibiotics, rather than presumed maternal transmission, delays microbiome development and prevents the early differentiation based on body site regardless of delivery mode. Metabolomic analyses identify the development of all gut metabolomes of preterm infants toward full-term infant profiles, but a significant increase of primary bile acid metabolism only in the non-antibiotic treated vaginally birthed late preterm infants. This study provides a framework for future multi-omic, multibody site analyses on these high-risk preterm infant populations and suggests opportunities for monitoring and intervention, with infant antibiotic exposure as the primary driver of delays in microbiome development.

The molecular impact of life in an indoor environment

The chemistry of indoor surfaces and the role of microbes in shaping and responding to that chemistry are largely unexplored. We found that, over 1 month, people's presence and activities profoundly reshaped the chemistry of a house. Molecules associated with eating/cooking, bathroom use, and personal care were found throughout the entire house, while molecules associated with medications, outdoor biocides, and microbially derived compounds were distributed in a location-dependent manner. The house and its microbial occupants, in turn, also introduced chemical transformations such as oxidation and transformations of foodborne molecules. The awareness of and the ability to observe the molecular changes introduced by people should influence future building designs.

The Host-Microbiome Response to Hyperbaric Oxygen Therapy in Ulcerative Colitis Patients

BACKGROUND & AIMS

Hyperbaric oxygen therapy (HBOT) is a promising treatment for moderate-to-severe ulcerative colitis. However, our current understanding of the host and microbial response to HBOT remains unclear. This study examined the molecular mechanisms underpinning HBOT using a multi-omic strategy.

METHODS

Pre- and post-intervention mucosal biopsies, tissue, and fecal samples were collected from HBOT phase 2 clinical trials. Biopsies and fecal samples were subjected to shotgun metaproteomics, metabolomics, 16s rRNA sequencing, and metagenomics. Tissue was subjected to bulk RNA sequencing and digital spatial profiling (DSP) for single-cell RNA and protein analysis, and immunohistochemistry was performed. Fecal samples were also used for colonization experiments in IL10-/- germ-free UC mouse models.

RESULTS

Proteomics identified negative associations between HBOT response and neutrophil azurophilic granule abundance. DSP identified an HBOT-specific reduction of neutrophil STAT3, which was confirmed by immunohistochemistry. HBOT decreased microbial diversity with a proportional increase in Firmicutes and a secondary bile acid lithocholic acid. A major source of the reduction in diversity was the loss of mucus-adherent taxa, resulting in increased MUC2 levels post-HBOT. Targeted database searching revealed strain-level associations between Akkermansia muciniphila and HBOT response status. Colonization of IL10-/- with stool obtained from HBOT responders resulted in lower colitis activity compared with non-responders, with no differences in STAT3 expression, suggesting complementary but independent host and microbial responses.

CONCLUSIONS

HBOT reduces host neutrophil STAT3 and azurophilic granule activity in UC patients and changes in microbial composition and metabolism in ways that improve colitis activity. Intestinal microbiota, especially strain level variations in A muciniphila, may contribute to HBOT non-response.

Perspective: A Framework for Addressing Dynamic Food Consumption Processes

The study of food consumption, diet, and related concepts is motivated by diverse goals, including understanding why food consumption impacts our health, and why we eat the foods we do. These varied motivations can make it challenging to define and measure consumption, as it can be specified across nearly infinite dimensions-from micronutrients to carbon footprint to food preparation. This challenge is amplified by the dynamic nature of food consumption processes, with the underlying phenomena of interest often based on the nature of repeated interactions with food occurring over time. This complexity underscores a need to not only improve how we measure food consumption but is also a call to support theoreticians in better specifying what, how, and why food consumption occurs as part of processes, as a prerequisite step to rigorous measurement. The purpose of this Perspective article is to offer a framework, the consumption process framework, as a tool that researchers in a theoretician role can use to support these more robust definitions of consumption processes. In doing so, the framework invites theoreticians to be a bridge between practitioners who wish to measure various aspects of food consumption and methodologists who can develop measurement protocols and technologies that can support measurement when consumption processes are clearly defined. In the paper we justify the need for such a framework, introduce the consumption process framework, illustrate the framework via a use case, and discuss existing technologies that enable the use of this framework and, by extension, more rigorous study of consumption. This consumption process framework demonstrates how theoreticians could fundamentally shift how food consumption is defined and measured towards more rigorous study of what, how, and why food is eaten as part of dynamic processes and a deeper understanding of linkages between behavior, food, and health.

Native mass spectrometry-based metabolomics identifies metal-binding compounds

Although metals are essential for the molecular machineries of life, systematic methods for discovering metal-small molecule complexes from biological samples are limited. Here, we describe a two-step native electrospray ionization-mass spectrometry method, in which post-column pH adjustment and metal infusion are combined with ion identity molecular networking, a rule-based data analysis workflow. This method enabled the identification of metal-binding compounds in complex samples based on defined mass (m/z) offsets of ion species with the same chromatographic profiles. As this native electrospray metabolomics approach is suited to the use of any liquid chromatography-mass spectrometry system to explore the binding of any metal, this method has the potential to become an essential strategy for elucidating metal-binding molecules in biology.

Chemical Proportionality within Molecular Networks

Molecular networking of non-targeted tandem mass spectrometry data connects structurally related molecules based on similar fragmentation spectra. Here, we report the Chemical Proportionality (ChemProp) contextualization of molecular networks. ChemProp scores the changes of abundance between two connected nodes over sequential data series (e.g., temporal or spatial relationships), which can be displayed as a direction within the network to prioritize potential biological and chemical transformations or proportional changes of (biosynthetically) related compounds. We tested the ChemProp workflow on a ground truth data set of a defined mixture and highlighted the utility of the tool to prioritize specific molecules within biological samples, including bacterial transformations of bile acids, human drug metabolism, and bacterial natural products biosynthesis. The ChemProp workflow is freely available through the Global Natural Products Social Molecular Networking (GNPS) environment.

Ion identity molecular networking for mass spectrometry-based metabolomics in the GNPS environment

Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. As a result, the fragmentation spectra of these ion species often remain unconnected in tandem mass spectrometry-based molecular networks, leading to redundant and disconnected sub-networks of the same compound classes. To overcome this bottleneck, we develop Ion Identity Molecular Networking (IIMN) that integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. The new feature relationships improve network connectivity for structurally related molecules, can be used to reveal unknown ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral reference libraries. IIMN is integrated into various open source feature finding tools and the GNPS environment. Moreover, IIMN-based spectral libraries with a broad coverage of ion species are publicly available.

A community resource for paired genomic and metabolomic data mining

Genomics and metabolomics are widely used to explore specialized metabolite diversity. The Paired Omics Data Platform is a community initiative to systematically document links between metabolome and (meta)genome data, aiding identification of natural product biosynthetic origins and metabolite structures.

ReDU: a framework to find and reanalyze public mass spectrometry data

We present ReDU ( https://redu.ucsd.edu/ ), a system for metadata capture of public mass spectrometry-based metabolomics data, with validated controlled vocabularies. Systematic capture of knowledge enables the reanalysis of public data and/or co-analysis of one's own data. ReDU enables multiple types of analyses, including finding chemicals and associated metadata, comparing the shared and different chemicals between groups of samples, and metadata-filtered, repository-scale molecular networking.

Reproducible molecular networking of untargeted mass spectrometry data using GNPS

Global Natural Product Social Molecular Networking (GNPS) is an interactive online small molecule-focused tandem mass spectrometry (MS2) data curation and analysis infrastructure. It is intended to provide as much chemical insight as possible into an untargeted MS2 dataset and to connect this chemical insight to the user's underlying biological questions. This can be performed within one liquid chromatography (LC)-MS2 experiment or at the repository scale. GNPS-MassIVE is a public data repository for untargeted MS2 data with sample information (metadata) and annotated MS2 spectra. These publicly accessible data can be annotated and updated with the GNPS infrastructure keeping a continuous record of all changes. This knowledge is disseminated across all public data; it is a living dataset. Molecular networking-one of the main analysis tools used within the GNPS platform-creates a structured data table that reflects the molecular diversity captured in tandem mass spectrometry experiments by computing the relationships of the MS2 spectra as spectral similarity. This protocol provides step-by-step instructions for creating reproducible, high-quality molecular networks. For training purposes, the reader is led through a 90- to 120-min procedure that starts by recalling an example public dataset and its sample information and proceeds to creating and interpreting a molecular network. Each data analysis job can be shared or cloned to disseminate the knowledge gained, thus propagating information that can lead to the discovery of molecules, metabolic pathways, and ecosystem/community interactions.

Global chemical effects of the microbiome include new bile-acid conjugations

A mosaic of cross-phylum chemical interactions occurs between all metazoans and their microbiomes. A number of molecular families that are known to be produced by the microbiome have a marked effect on the balance between health and disease^1-9. Considering the diversity of the human microbiome (which numbers over 40,000 operational taxonomic units¹⁰), the effect of the microbiome on the chemistry of an entire animal remains underexplored. Here we use mass spectrometry informatics and data visualization approaches^11-13 to provide an assessment of the effects of the microbiome on the chemistry of an entire mammal by comparing metabolomics data from germ-free and specific-pathogen-free mice. We found that the microbiota affects the chemistry of all organs. This included the amino acid conjugations of host bile acids that were used to produce phenylalanocholic acid, tyrosocholic acid and leucocholic acid, which have not previously been characterized despite extensive research on bile-acid chemistry¹⁴. These bile-acid conjugates were also found in humans, and were enriched in patients with inflammatory bowel disease or cystic fibrosis. These compounds agonized the farnesoid X receptor in vitro, and mice gavaged with the compounds showed reduced expression of bile-acid synthesis genes in vivo. Further studies are required to confirm whether these compounds have a physiological role in the host, and whether they contribute to gut diseases that are associated with microbiome dysbiosis.

A UHPLC-HRMS based metabolomics and chemoinformatics approach to chemically distinguish 'super foods' from a variety of plant-based foods

The aim of this study was to investigate if the declared benefits associated with superfoods are related to a specific molecular composition. For this purpose, untargeted metabolomics and molecular networking were used to obtain an overview of all features, focusing on compounds with anti-inflammatory, antioxidant or antimicrobial properties. 565 plant-based food samples were analyzed using UHPLC-HRMS and advanced data analysis tools. The molecular networking of the whole dataset allowed identification of a greater diversity of molecules, in particular, prenol lipids, isoflavonoids and isoquinolines in superfoods, when compared with non-superfood species belonging to the same botanical family. Furthermore, in silico tools were used to expand our chemical knowledge of compounds observed in superfood samples.

Author Correction: Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Untargeted mass spectrometry-based metabolomics approach unveils molecular changes in raw and processed foods and beverages

In our daily lives, we consume foods that have been transported, stored, prepared, cooked, or otherwise processed by ourselves or others. Food storage and preparation have drastic effects on the chemical composition of foods. Untargeted mass spectrometry analysis of food samples has the potential to increase our chemical understanding of these processes by detecting a broad spectrum of chemicals. We performed a time-based analysis of the chemical changes in foods during common preparations, such as fermentation, brewing, and ripening, using untargeted mass spectrometry and molecular networking. The data analysis workflow presented implements an approach to study changes in food chemistry that can reveal global alterations in chemical profiles, identify changes in abundance, as well as identify specific chemicals and their transformation products. The data generated in this study are publicly available, enabling the replication and re-analysis of these data in isolation, and serve as a baseline dataset for future investigations.

Alternative Ready-To-Use Therapeutic Food Yields Less Recovery Than the Standard for Treating Acute Malnutrition in Children From Ghana

In Ghana, an alternative ready-to-use food (RUTF) formulation that met all specifications was not as good as standard RUTF in affecting recovery from acute malnutrition among children aged 6 to 59 months.

Background:

Only 20% of children with severe acute malnutrition (SAM) have access to ready-to-use therapeutic food (RUTF), and RUTF cost limits its accessibility.

Methods:

This randomized, double-blind controlled study involved a clinical equivalence trial comparing the effectiveness of an alternative RUTF with standard RUTF in the home-based treatment of uncomplicated SAM and moderate malnutrition in Ghanaian children aged 6 to 59 months. The primary outcome was recovery, equivalence was defined as being within 5 percentage points of the control group, and an intention-to-treat analysis was used. Alternative RUTF was composed of whey protein, soybeans, peanuts, sorghum, milk, sugar, and vegetable oil. Standard RUTF included peanuts, milk, sugar, and vegetable oil. The cost of alternative RUTF ingredients was 14% less than standard RUTF. Untargeted metabolomics was used to characterize the bioactive metabolites in the RUTFs.

Results:

Of the 1,270 children treated for SAM or moderate malnutrition, 554 of 628 (88%) receiving alternative RUTF recovered (95% confidence interval [CI]=85% to 90%) and 516 of 642 (80%) receiving standard RUTF recovered (95% CI=77% to 83%). The difference in recovery was 7.7% (95% CI=3.7% to 11.7%). Among the 401 children with SAM, the recovery rate was 130 of 199 (65%) with alternative RUTF and 156 of 202 (77%) with standard RUTF (P=.01). The default rate in SAM was 60 of 199 (30%) for alternative RUTF and 41 of 202 (20%) for standard RUTF (P=.04). Children enrolled with SAM who received alternative RUTF had less daily weight gain than those fed standard RUTF (2.4 ± 2.4 g/kg vs. 2.9 ± 2.6 g/kg, respectively; P<.05). Among children with moderate wasting, recovery rates were lower for alternative RUTF, 386 of 443 (87%), than standard RUTF, 397 of 426 (93%) (P=.003). More isoflavone metabolites were found in alternative RUTF than in the standard.

Conclusion:

The lower-cost alternative RUTF was less effective than standard RUTF in the treatment of severe and moderate malnutrition in Ghana.

Microbial tailoring of acyl peptidic siderophores

Marine bacteria produce an abundance of suites of acylated siderophores characterized by a unique, species-dependent headgroup that binds iron(III) and one of a series of fatty acid appendages. Marinobacter sp. DS40M6 produces a suite of seven acylated marinobactins, with fatty acids ranging from saturated and unsaturated C12–C18 fatty acids. In the present study, we report that in the late log phase of growth, the fatty acids are hydrolyzed by an amide hydrolase producing the peptidic marinobactin headgroup. Halomonas aquamarina str. DS40M3, another marine bacterium isolated originally from the same sample of open ocean water as Marinobacter sp. DS40M6, produces the acyl aquachelins, also as a suite composed of a peptidic headgroup distinct from that of the marinobactins. In contrast to the acyl marinobactins, hydrolysis of the suite of acyl aquachelins is not detected, even when H. aquamarina str. DS40M3 is grown into the stationary phase. The Marinobacter cell-free extract containing the acyl amide hydrolase is active toward exogenous acyl-peptidic siderophores (e.g., aquachelin C, loihichelin C, as well as octanoyl homoserine lactone used in quorum sensing). Further, when H. aquamarina str. DS40M3 is cultured together with Marinobacter sp. DS40M6, the fatty acids of both suites of siderophores are hydrolyzed, and the aquachelin headgroup is also produced. The present study demonstrates that coculturing bacteria leads to metabolically tailored metabolites compared to growth in a single pure culture, which is interesting given the importance of siderophore-mediated iron acquisition for bacterial growth and that Marinobacter sp. DS40M6 and H. aquamarina str. DS40M3 were isolated from the same sample of seawater.

Amphiphilic siderophore production by oil-associating microbes

Amphibactin siderophores have been isolated from oil-associatedVibriospp. following the Deepwater Horizon oil spill, and fromAlcanivorax borkumensisSK2.

Amino acid variability in the peptide composition of a suite of amphiphilic peptide siderophores from an open ocean Vibrio species

In response to iron-depleted aerobic conditions, bacteria often secrete low molecular weight, high-affinity iron(III)-complexing ligands, siderophores, to solubilize and sequester iron(III). Many marine siderophores are amphiphilic and are produced in suites, wherein each member within a particular suite has the same iron(III)-binding polar head group which is appended by one or two fatty acids of differing length, degree of unsaturation, and degree of hydroxylation, establishing the suite composition. We report the isolation and structural characterization of a suite of siderophores from marine bacterial isolate Vibrio sp. Nt1. On the basis of structural analysis, this suite of siderophores, the moanachelins, is amphiphilic and composed of two N-acetyl-N-hydroxy-D-ornithines, one N-acetyl-N-hydroxy-L-ornithine, and either a glycine or an L-alanine, appended with various saturated and unsaturated fatty acid tails. The variation in the small side-chain amino acid is the first occurrence of variation in the peptidic head group structure of a set of siderophores produced by a single bacterium.

A suite of citrate-derived siderophores from a marine Vibrio species isolated following the Deepwater Horizon oil spill

Nearly all microbes require iron for growth. The low concentration of iron found in the ocean makes iron acquisition a particularly difficult task. In response to these low iron conditions, many bacteria produce low-molecular-weight iron-binding molecules called siderophores to aid in iron uptake. We report herein the isolation and structural characterization of a suite of amphiphilic siderophores called the ochrobactins-OH, which are produced by a Vibrio species isolated from the Gulf of Mexico after the 2010 Deepwater Horizon oil spill. The citrate-based ochrobactins-OH are derivatives of aerobactin, replacing the acetyl groups with fatty acid appendages ranging in size from C8 to C12, and are distinctly different from the ochrobactins in that the fatty acid appendages are hydroxylated rather than unsaturated. The discovery of the marine amphiphilic ochrobactin-OH suite of siderophores increases the geographic and phylogenetic diversity of siderophore-producing bacteria.