Did you know?
Metallomic signatures can reveal hidden drivers of disease by mapping how trace metals like nickel, iron, and cadmium shape microbial behavior and immune responses. These signatures not only help identify toxic exposures but also spotlight metal-dependent pathogens, offering new targets for precision-guided therapies.
Metallomic Signatures
Researched by:
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Karen Pendergrass
ID
Karen Pendergrass
Karen Pendergrass is a microbiome researcher specializing in microbiome-targeted interventions (MBTIs). She systematically analyzes scientific literature to identify microbial patterns, develop hypotheses, and validate interventions. As the founder of the Microbiome Signatures Database, she bridges microbiome research with clinical practice. In 2012, based on her own investigative research, she became the first documented case of FMT for Celiac Disease—four years before the first published case study.
A metallomic signature is the condition-specific profile of trace metals and metal-binding molecules that reflects disrupted metal homeostasis.
Research feed -
Karen Pendergrass
Researched by:
-
Karen Pendergrass
ID
Karen Pendergrass
Microbiome Signatures identifies and validates condition-specific microbiome shifts and interventions to accelerate clinical translation. Our multidisciplinary team supports clinicians, researchers, and innovators in turning microbiome science into actionable medicine.
Karen Pendergrass
Overview 
FAQs 
Research Feed Overview
Metallomic signatures refer to the condition-specific profile of trace metals and metal-binding molecules that reflect disruptions in metal homeostasis. This signature captures both host and microbial interactions with metals such as iron, zinc, copper, nickel, lead, and cadmium, and is commonly assessed through tissue, blood, or microbiome samples. Metallomic data integrates with other omics layers such as genomic, metabolomic, proteomic, and microbiome signatures to illuminate upstream drivers of disease. This is particularly valuable in conditions influenced by environmental exposures, systemic inflammation, or chronic immune activation.
Metallomic Signatures in Pathogenesis and Etiology
A wide array of diseases have been linked to perturbations in metal homeostasis. By comparing the metallomic signatures of healthy versus diseased subjects (or tissues), such as those with neurodegenerative diseases, scientists are uncovering how dysregulated metal levels contribute to disease development and progression.
Relevance to Microbiome Research
Metallomic signatures are deeply connected to microbial metallomics, the study of how microbes acquire, regulate, and utilize metals for metabolic processes and survival. Many pathogenic or dysbiosis-associated taxa rely on metal co-factors like nickel, iron, and zinc to activate virulence factors, resist oxidative stress, or establish biofilms. In metal-enriched environments, these microbes gain a competitive advantage, outcompeting commensals that lack similar metal-handling systems. As a result, metallomic signatures often mirror microbiome signatures, especially in conditions where trace metal excess selects for the expansion of metal-tolerant or metal-dependent microbial taxa.
Clinical Utility
Metallomic signatures provide critical clinical insights by revealing trace metal imbalances that contribute to microbial selection, immune dysregulation, and chronic inflammation. These imbalances can alter the composition and behavior of microbial communities, allowing metal-tolerant pathogens to outcompete metal-sensitive commensals and gain functional advantages. Many of these enriched taxa exploit metals as co-factors for virulence enzymes—such as urease, a nickel-dependent enzyme that facilitates epithelial invasion, immune evasion, and pH modification. Elevated metal levels can therefore establish a biochemical niche that supports both the survival and pathogenicity of harmful species. By identifying these dynamics, metallomic signatures offer a mechanistic framework for understanding the interactions between environmental metal exposure, microbial behavior, and host response. Therapeutic strategies that target metal-induced microbial shifts—such as dietary metal modulation, chelation therapies, or suppression of metal-reliant taxa—not only restore microbial balance but also validate the corresponding microbiome signature. This dual alignment supports precision-guided interventions that are informed by both ecological and biochemical disease mechanisms.
Biomarker Potential of Metallomic Signatures
Metallomic signatures are emerging as sensitive, non-invasive biomarkers for disease diagnosis, monitoring, and stratification. These profiles include not only absolute metal concentrations but also natural isotope ratios (e.g., δ66/64Zn), metal–metal interactions, and element-to-element ratios that reflect systemic dyshomeostasis. In diseases such as cancer, COPD, and chronic inflammatory disorders, metallomic patterns involving both toxic and essential metals have demonstrated strong discriminatory power, often exceeding that of conventional biomarkers. Because metal perturbations can occur early in disease progression and remain stable over time, metallomic signatures offer considerable promise for early detection and risk prediction. When applied within microbiome-targeted intervention frameworks, they further aid in identifying pathogenic taxa that depend on specific metals for virulence, thereby reinforcing the validity of both the microbial and metallomic dimensions of disease. Taken together, these signatures provide a rich, actionable layer of insight for both translational research and clinical decision-making.
FAQs
Why are metals important in microbiome research?
Why are metals important in microbiome research?
Metals are essential cofactors in numerous microbial enzymes, but in excess, they can exert selective pressure, favoring metal-tolerant or metal-dependent pathogens. Metallomic analysis helps explain why certain microbes thrive or decline in specific conditions, particularly in chronic inflammation, cancer, or heavy-metal-exposed environments. It complements taxonomic and metabolomic analyses by illuminating microbial trait selection driven by host and environmental metal availability.
How is a metallomic signature different from a taxonomic signature?
How is a metallomic signature different from a taxonomic signature?
While taxonomic signatures focus on which microbes are present or altered in a condition, metallomic signatures focus on why those microbes persist—highlighting their metal acquisition genes, resistance mechanisms, or dependence on metal cofactors. Metallomics adds a functional, mechanistic layer that can improve the explanatory and predictive power of a microbiome signature.
What are examples of microbial traits captured in metallomic signatures?
What are examples of microbial traits captured in metallomic signatures?
Metallomic traits include urease activity (nickel-dependent), superoxide dismutase isoforms (copper/zinc-dependent), siderophore production (iron scavenging), efflux pump regulation (cadmium, arsenic, lead), and resistance genes for heavy metals. These are typically tied to virulence, biofilm formation, oxidative stress resistance, or metabolic adaptation.
Research Feed
Urine metallomics signature as an indicator of pancreatic cancer†
May 20, 2020
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Metals •
Metals
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This study identifies a distinct urinary metallomic signature in pancreatic cancer patients, marked by altered calcium, magnesium, copper, and zinc levels, along with lighter zinc isotopic composition. These findings suggest that non-invasive urine tests could enable early PDAC detection by leveraging trace metal imbalances and stable isotope shifts.
What was studied?
This study explored the utility of urinary metallomic profiling—specifically concentrations and isotopic composition of essential metals—as a non-invasive diagnostic tool for pancreatic ductal adenocarcinoma (PDAC). The researchers examined urine samples from PDAC patients and healthy controls to identify specific metal dyshomeostasis and isotopic shifts that could serve as biomarkers for PDAC detection.
Who was studied?
Urine samples from 21 patients diagnosed with PDAC and 46 healthy control subjects were analyzed. All samples were collected under ethical approval through the Barts Pancreas Tissue Bank.
Most important findings:
A distinct urinary metallomic signature was identified in pancreatic ductal adenocarcinoma (PDAC) patients, characterized by decreased calcium and magnesium and increased zinc and copper levels. The multivariate model integrating these four elements exhibited outstanding diagnostic accuracy, achieving an area under the curve (AUC) of 0.995 with 99.5% sensitivity. Moreover, stable zinc isotope analysis revealed a shift toward isotopically lighter zinc in PDAC patients (median δ⁶⁶Zn = −0.15‰) compared to healthy controls (median δ⁶⁶Zn = +0.02‰), likely due to oxidative stress-induced oxidation of cysteine-rich metallothioneins, which preferentially bind lighter isotopes. From a microbiome-metallomic perspective, such trace metal imbalances—particularly involving zinc and copper—may influence microbial community structure by selectively enriching pathogenic taxa and diminishing beneficial ones. Although the microbiome was not directly assessed in this study, the metallomic disturbances observed may serve as indirect indicators of host-microbe dysregulation, especially relevant in gastrointestinal malignancies such as PDAC.
| Element | Change in PDAC vs. Control |
|---|---|
| Calcium (Ca) | Decreased (***p <0.0001) |
| Magnesium (Mg) | Decreased (**p = 0.0002) |
| Zinc (Zn) | Increased (*p = 0.015) |
| Copper (Cu) | Increased (*p = 0.02) |
Greatest implications of the study:
This work provides strong preliminary evidence that urinary metallomic profiles—specifically Ca, Mg, Cu, Zn concentrations and zinc isotopic signatures—can serve as non-invasive biomarkers for PDAC detection. It is the first study to report isotopic zinc alterations in urine associated with PDAC and proposes a compelling mechanistic link to oxidative stress and metalloprotein dysregulation. If validated in larger cohorts, this approach could represent a breakthrough in early detection of pancreatic cancer, a malignancy notorious for its asymptomatic progression and poor prognosis. The authors propose that isotopic measurements, which offer significantly greater resolution than standard clinical assays, could even function as prognostic tools if longitudinally correlated with disease progression.
Metallomic analysis of brain tissues distinguishes between cases of dementia with Lewy bodies, Alzheimer’s disease, and Parkinson’s disease dementia
June 26, 2024
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Metallomic Signatures •
Metallomic Signatures
Did you know?
Metallomic signatures can reveal hidden drivers of disease by mapping how trace metals like nickel, iron, and cadmium shape microbial behavior and immune responses. These signatures not only help identify toxic exposures but also spotlight metal-dependent pathogens, offering new targets for precision-guided therapies.
Dementia with Lewy bodies (DLB) brains show widespread copper depletion and region-specific sodium, manganese, iron, and selenium alterations. While copper loss is common to AD and PDD, DLB presents a distinct metallomic fingerprint, enabling disease differentiation via PCA. Metallomic profiling may aid in diagnosing overlapping dementias and reveals unique pathophysiological signatures.
What was studied?
This original research study investigated whether the metallomic profile of dementia with Lewy bodies (DLB) differs from that of Alzheimer’s disease (AD) and Parkinson’s disease dementia (PDD). The study sought to determine if post-mortem changes in elemental concentrations—particularly in essential metals—could help differentiate these often-overlapping neurodegenerative conditions. Using ICP-MS (Inductively Coupled Plasma–Mass Spectrometry), the authors quantified concentrations of nine elements (Na, Mg, K, Ca, Mn, Fe, Cu, Zn, and Se) across 10 brain regions from DLB patients and age-/sex-matched controls. These findings were directly compared to previously published metallomic profiles for AD and PDD, produced using identical methodologies. Multivariate analyses (PCA and PLS-DA) were employed to assess the potential for disease discrimination based on metal signatures.
Who was studied?
The study analyzed post-mortem brain tissue from 23 DLB patients and 20 controls, collected across ten distinct brain regions. Comparative analyses included prior datasets from similarly matched AD and PDD patient cohorts.
What were the most important findings?
n this study, region-specific metallomic profiling revealed distinct trace element alterations in Dementia with Lewy Bodies (DLB). Copper (Cu) levels were consistently decreased in five of ten DLB brain regions, including the cingulate gyrus (CG), middle temporal gyrus (MTG), primary visual cortex (PVC), substantia nigra (SN), and putamen (PUT), suggesting a widespread Cu deficiency. Sodium (Na) was elevated in four regions—medulla (MED), cerebellum (CB), MTG, and CG—while more localized changes were observed for other metals. Iron (Fe) levels were increased in the motor cortex (MCX) and CG, whereas manganese (Mn) was decreased in both the PVC and MED. Calcium (Ca) was specifically reduced in the hippocampus, and selenium (Se) was also decreased in the PVC. No significant differences in magnesium, potassium, or zinc levels were observed between DLB and control brains. Multivariate analyses, including Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA), demonstrated that DLB could be distinctly separated from Alzheimer’s disease (AD) and Parkinson’s disease dementia (PDD) based on metallomic signatures. Specifically, CG, MTG, and PVC profiles enabled discrimination between DLB and AD, while the PVC alone differentiated DLB from PDD. Notably, copper depletion emerged as the only common alteration across DLB, AD, and PDD, underscoring its potential central role in the pathogenesis of neurodegenerative diseases. The authors propose that these metallomic fingerprints may reflect disease-specific mechanisms, including variations in oxidative stress, protein aggregation, and mitochondrial dysfunction.
What are the greatest implications of this study?
This study provides compelling evidence that distinct metallomic signatures exist across DLB, AD, and PDD, despite shared pathology such as copper depletion. It strengthens the emerging concept that trace metal dysregulation is disease-specific, rather than a general byproduct of neurodegeneration. The findings support the idea that metallomic profiling—potentially via cerebrospinal fluid or advanced imaging in living patients—could improve differential diagnosis of dementias with overlapping clinical features. Furthermore, the study reinforces the hypothesis that metal dyshomeostasis, particularly copper depletion, may be a contributing pathogenic mechanism, impairing antioxidant defenses and mitochondrial function. These findings could inform new diagnostic tools and therapeutic targets.
Zinc
Zinc is an essential trace element vital for cellular functions and microbiome health. It influences immune regulation, pathogen virulence, and disease progression in conditions like IBS and breast cancer. Pathogens exploit zinc for survival, while therapeutic zinc chelation can suppress virulence, rebalance the microbiome, and offer potential treatments for inflammatory and degenerative diseases.
Nickel
Bacteria regulate transition metal levels through complex mechanisms to ensure survival and adaptability, influencing both their physiology and the development of antimicrobial strategies.
Microbiome Signatures Definition: A Conceptual Advancement for Translational Microbiome Science
Microbiome signatures are reproducible ecological and functional patterns—encompassing traits, interactions, and metabolic functions—that reflect microbial adaptation to specific host or environmental states. Beyond taxonomy, they capture conserved features like metal metabolism or immune modulation, enabling systems-level diagnosis and intervention in health and disease.
Microbial Metallomics
Microbial Metallomics is the study of how microorganisms interact with metal ions in biological systems, particularly within the human microbiome.
Metallomic Signatures
A metallomic signature is the condition-specific profile of trace metals and metal-binding molecules that reflects disrupted metal homeostasis.