bioRxiv Science⌕ Search

bioRxiv · 10.1101/2025.11.05.686764

Inverse stable isotope labeling (InverSIL) links predicted catecholate siderophore gene clusters to their products in diverse bacteria

Abstract

Bacteria produce high-affinity iron-chelating secondary metabolites called siderophores to access insoluble Fe(III) in their environments. Genome mining has revealed many predicted siderophore biosynthetic gene clusters (BGCs) in bacterial genomes, however the structures of their siderophore products remain mostly undetermined. This limits our molecular-level understanding of how bacteria acquire iron, as well as how they interact with other taxa that may use the same siderophores within bacterial communities. Here, we apply inverse stable isotope labeling (InverSIL) to rapidly connect predicted siderophore BGCs to their products. With InverSIL, bacteria are grown on 13C-substituted carbon sources and then fed predicted biosynthetic precursors at their natural isotopic abundance to identify BGC products by mass spectrometry, which removes issues with the availability of isotopically substituted precursors. We use InverSIL to determine the structures of the siderophore products of predicted BGCs from the methylotrophic genera Methylophilus and Methylobacterium, and the siderophores produced by the opportunistic pathogen Chromobacterium violaceum, which were previously shown to be essential for virulence yet remained structurally uncharacterized. We next use this approach to reveal the unexpected production of enterobactin by the genera Kushneria and Paracoccus, which was difficult to predict from genome sequences due to the distributed nature of the biosynthetic genes within the genomes. Finally, we use InverSIL to discover new siderophores, cellulochelin A and B, from the cellulose-degrading plant symbiont Cellulomonas sp. strain Leaf334. These findings demonstrate the utility of InverSIL for functional BGC characterization and expand our molecular understanding of bacterial iron acquisition strategies. IMPORTANCEIron acquisition is essential for microbial survival, and bacteria produce secondary metabolites called siderophores to scavenge iron from the environment. While bacterial genome sequences show many predicted genes for making siderophores, most remain unlinked to their metabolic products. Understanding which siderophores bacteria produce is critical for elucidating microbial iron acquisition strategies, ecological interactions, and potential roles in host-microbe interactions. Here, we demonstrate how inverse stable isotope labeling (InverSIL) can rapidly link predicted siderophore gene clusters to their corresponding metabolites. By applying InverSIL to diverse bacterial strains, we validate known siderophore products and uncover unexpected products, highlighting the limitations of current in silico predictions. This study highlights the value of combining experimental approaches with genome mining to advance our understanding of how bacteria interact with each other and their environment.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Robes, J. M. D., Liebergesell, T. C. E., Medvedeva, V. P., Puri, A. W.. 2025-11-05. Inverse stable isotope labeling (InverSIL) links predicted catecholate siderophore gene clusters to their products in diverse bacteria. https://doi.org/10.1101/2025.11.05.686764

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Reverse Transcription Loop-Mediated Isothermal Amplification Combined with Lateral Flow Assay (RT-LAMP-LFA) for Rapid Detection of the 2026 Bundibugyo Virus (BDBV) Outbreak Strain

Making accurate diagnosis is a critical first step in patient management and control for emerging and re-emerging disease outbreaks. Bundibugyo virus (BDBV) is a filovirus that causes Ebola disease, and the 2026 outbreak highlights the need for rapid diagnostic approaches that can be deployed in settings with limited laboratory infrastructure. Here, we developed a reverse transcription loop-mediated isothermal amplification-lateral flow assay (RT-LAMP-LFA) for rapid detection of the 2026 BDBV outbreak strain. LAMP primers were designed based on the genome sequence of the 2026 outbreak strain, and the conservation of the primer binding sites among all available 2026 outbreak genomes was confirmed in silico. LAMP primers were evaluated for analytical specificity and sensitivity using in vitro-transcribed RNA (ivtRNA) from BDBV and other filoviruses, as well as RNA derived from arboviruses and mammalian cells. Amplification products were detected using a Chromatography-Printed Array Strip (C-PAS) lateral flow platform. The newly designed primers specifically detected the presence of BDBV RNA without nonspecific amplification of the other viral or cellular RNA samples tested. Consistent amplification was observed down to 103 copies per reaction. In addition, BDBV viral RNA was successfully amplified, and the amplification products were detected using C-PAS, with the total workflow being completed within 25 min. These findings demonstrate the analytical specificity and sensitivity of the developed RT-LAMP-LFA assay and its compatibility with rapid visual lateral flow detection, supporting its potential application as a point-of-care approach for BDBV detection.

microbiology↗

Divergent methane production and microbial community responses to carbon enrichment in freshwater wetland sediments

Methane (CH4) accumulation in wetland sediments reflects interactions among organic matter, sediment chemistry, and microbial communities. We combined depth-resolved field characterization across four wetland habitats in northern Israel with complementary incubations to examine methane accumulation and responses to labile-carbon enrichment. Sediment cores were characterized using Rock-Eval analysis, porewater chemistry, oxygen profiling at three sites, and mcrA amplicon sequencing. High CH4 concentrations occurred under contrasting conditions: Ein Nimfit (EN) contained approximately 12% total organic carbon and reached 2.1 mM CH4, whereas Ein Afek site EA2 contained approximately 5% carbon and accumulated 0.7-1.7 mM CH4. Both showed sulfate depletion, but EN exhibited pronounced sulfide accumulation, whereas EA2 showed greater dissolved iron and nutrient enrichment. Their classified methanogenic assemblages also differed. EA1 remained methane poor despite increasing carbon content with depth, while EA3 combined low carbon content and CH4 accumulation with detectable methanogens and lower methanogenic diversity. In a 36-day bottle experiments using sediments from two of the four wetland habitats, sucrose-amended EA3 exhibited a transient maximum of 18.8 mmol collected CH4 kg-1 wet sediment during Days 22-29, whereas EN reached its highest collected amount during Days 29-36. Methane proportions increased before the large output increase in EA3 but remained comparatively stable and high in EN. Soluble chemical oxygen demand trajectories and microbial community changes also differed. These findings identify distinct biogeochemical settings supporting methane accumulation and demonstrate methanogenic potential in low-CH4 sediment, emphasizing the complementary information provided by field profiles, microbial characterization, and exploratory enrichment experiments.

microbiology↗

The absence of microbiome in germ-free mice exacerbates the pathogenicity of mouse-adapted SARS-CoV-2 MA10

Germ-free mice, which are devoid of microbiota, provide a powerful system to define the contribution of the microbiome to host responses during infection. Severe COVID-19 outcomes are associated with multiple comorbidities that are themselves characterized by microbiome dysbiosis; however, the causal role of the microbiota in SARS-CoV-2 pathogenesis remains poorly understood. Here, we use germ-free mouse models to evaluate the impact of the microbiome on disease severity following infection with mouse-adapted SARS-CoV-2 MA10. Comparison with conventionally housed mice revealed that the absence of the microbiome markedly exacerbates SARS-CoV-2-induced disease in both C57BL/6 and Swiss Webster backgrounds. Germ-free mice exhibited greater weight loss, impaired lung function, worsened pulmonary pathology, and pronounced alterations in circulating cytokine and chemokine profiles compared with conventional controls. These findings show that resident microbiota limit SARS-CoV-2 pathogenicity and establish germ-free COVID-19 models as a powerful platform to identify protective microbial taxa and microbiota-based interventions to reduce severe disease.

microbiology↗