Stephanann M. Costello
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Stephanann M. Costello has a total of 21 co-authors. Here are the top co-authors by number of shared publications:
- Brian Tripet
Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT 59715, USA
3 shared publications - Valérie Copié
Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT 59715, USA
3 shared publications - Alexandra M. Cheney
Biochemistry and Chemistry, Montana State University
1 shared publication - Amanda L. Fuchs
National Institutes of Health
1 shared publication - Anastasia Schultz
Department of Microbiology and Cell Biology Montana State University Bozeman Montana USA
1 shared publication - Annie Waldum
Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT 59717, USA
1 shared publication
Latest Publications
- Open Access
- 1 May 2026
- Published by AIP Publishing in Structural Dynamics
- Vol. 13 (3)
13C NMR as a foundation for machine learning models of polysaccharides
Polysaccharide structural assignment via nuclear magnetic resonance (NMR) spectroscopy remains an analytical challenge due to spectral overlap because of limited chemical shift dispersion. This challenge is exacerbated by the wide-spread use of proton (1H) detection. Progress has also been hindered by the dispersed nature of carbohydrate databases and the restricted applicability of most prediction tools, which provide limited atom-specific residue discrimination in larger polymers. These limitations hamper the efficient characterization of glycosyltransferase (GT) activity, which depends on defining donor–acceptor substrate pairs and accurately identifying corresponding products. Here, we demonstrate the utility of high field 13C-detected NMR for the assignment of two homohexamers. Laminarihexaose and xylohexaose were analyzed using 2D heteronuclear correlation and correlation via long-range coupling (COLOC) experiments to evaluate whether complete residue level assignments could be achieved. The COLOC experiment revealed long range correlations that were not resolved using heteronuclear multiple bond correlation, and the 1D 13C spectra provided exceptional resolution, including distinct shoulders corresponding to residue specific chemical shift differences previously assumed to be indistinguishable. These findings suggest that high field 13C NMR can provide the nuanced atom level information required to train machine learning models for predicting chemical shift assignments of large, complex, and highly degenerate polysaccharides. Such models offer a promising framework for rapid structural identification of GT reaction products, enabling progress of high throughput characterization of plant derived polysaccharides central to renewable biomaterial development.
- 1 May 2026
- Published by AIP Publishing in Structural Dynamics
- Vol. 13 (3)
Open Access13C NMR as a foundation for machine learning models of polysaccharides
Polysaccharide structural assignment via nuclear magnetic resonance (NMR) spectroscopy remains an analytical challenge due to spectral overlap because of limited chemical shift dispersion. This challenge is exacerbated by the wide-spread use of proton (1H) detection. Progress has also been hindered by the dispersed nature of carbohydrate databases and the restricted applicability of most prediction tools, which provide limited atom-specific residue discrimination in larger polymers. These limitations hamper the efficient characterization of glycosyltransferase (GT) activity, which depends on defining donor–acceptor substrate pairs and accurately identifying corresponding products. Here, we demonstrate the utility of high field 13C-detected NMR for the assignment of two homohexamers. Laminarihexaose and xylohexaose were analyzed using 2D heteronuclear correlation and correlation via long-range coupling (COLOC) experiments to evaluate whether complete residue level assignments could be achieved. The COLOC experiment revealed long range correlations that were not resolved using heteronuclear multiple bond correlation, and the 1D 13C spectra provided exceptional resolution, including distinct shoulders corresponding to residue specific chemical shift differences previously assumed to be indistinguishable. These findings suggest that high field 13C NMR can provide the nuanced atom level information required to train machine learning models for predicting chemical shift assignments of large, complex, and highly degenerate polysaccharides. Such models offer a promising framework for rapid structural identification of GT reaction products, enabling progress of high throughput characterization of plant derived polysaccharides central to renewable biomaterial development.
- Open Access
- 31 July 2024
- Published by MDPI AG in Metabolites
- Vol. 14 (8) , 423
Metabolic Deficits in the Retina of a Familial Dysautonomia Mouse Model
Neurodegenerative retinal diseases such as glaucoma, diabetic retinopathy, Leber’s hereditary optic neuropathy (LHON), and dominant optic atrophy (DOA) are marked by progressive death of retinal ganglion cells (RGC). This decline is promoted by structural and functional mitochondrial deficits, including electron transport chain (ETC) impairments, increased oxidative stress, and reduced energy (ATP) production. These cellular mechanisms associated with progressive optic nerve atrophy have been similarly observed in familial dysautonomia (FD) patients, who experience gradual loss of visual acuity due to the degeneration of RGCs, which is thought to be caused by a breakdown of mitochondrial structures, and a disruption in ETC function. Retinal metabolism plays a crucial role in meeting the elevated energetic demands of this tissue, and recent characterizations of FD patients’ serum and stool metabolomes have indicated alterations in central metabolic processes and potential systemic deficits of taurine, a small molecule essential for retina and overall eye health. The present study sought to elucidate metabolic alterations that contribute to the progressive degeneration of RGCs observed in FD. Additionally, a critical subpopulation of retinal interneurons, the dopaminergic amacrine cells, mediate the integration and modulation of visual information in a time-dependent manner to RGCs. As these cells have been associated with RGC loss in the neurodegenerative disease Parkinson’s, which shares hallmarks with FD, a targeted analysis of the dopaminergic amacrine cells and their product, dopamine, was also undertaken. One dimensional (1D) proton (1H) nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry, and retinal histology methods were employed to characterize retinae from the retina-specific Elp1 conditional knockout (CKO) FD mouse model (Pax6-Cre; Elp1LoxP/LoxP). Metabolite alterations correlated temporally with progressive RGC degeneration and were associated with reduced mitochondrial function, alterations in ATP production through the Cahill and mini-Krebs cycles, and phospholipid metabolism. Dopaminergic amacrine cell populations were reduced at timepoints P30–P90, and dopamine levels were 25–35% lower in CKO retinae compared to control retinae at P60. Overall, this study has expanded upon our current understanding of retina pathology in FD. This knowledge may apply to other retinal diseases that share hallmark features with FD and may help guide new avenues for novel non-invasive therapeutics to mitigate the progressive optic neuropathy in FD.
- 31 July 2024
- Published by MDPI AG in Metabolites
- Vol. 14 (8) , 423
Open AccessMetabolic Deficits in the Retina of a Familial Dysautonomia Mouse Model
Neurodegenerative retinal diseases such as glaucoma, diabetic retinopathy, Leber’s hereditary optic neuropathy (LHON), and dominant optic atrophy (DOA) are marked by progressive death of retinal ganglion cells (RGC). This decline is promoted by structural and functional mitochondrial deficits, including electron transport chain (ETC) impairments, increased oxidative stress, and reduced energy (ATP) production. These cellular mechanisms associated with progressive optic nerve atrophy have been similarly observed in familial dysautonomia (FD) patients, who experience gradual loss of visual acuity due to the degeneration of RGCs, which is thought to be caused by a breakdown of mitochondrial structures, and a disruption in ETC function. Retinal metabolism plays a crucial role in meeting the elevated energetic demands of this tissue, and recent characterizations of FD patients’ serum and stool metabolomes have indicated alterations in central metabolic processes and potential systemic deficits of taurine, a small molecule essential for retina and overall eye health. The present study sought to elucidate metabolic alterations that contribute to the progressive degeneration of RGCs observed in FD. Additionally, a critical subpopulation of retinal interneurons, the dopaminergic amacrine cells, mediate the integration and modulation of visual information in a time-dependent manner to RGCs. As these cells have been associated with RGC loss in the neurodegenerative disease Parkinson’s, which shares hallmarks with FD, a targeted analysis of the dopaminergic amacrine cells and their product, dopamine, was also undertaken. One dimensional (1D) proton (1H) nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry, and retinal histology methods were employed to characterize retinae from the retina-specific Elp1 conditional knockout (CKO) FD mouse model (Pax6-Cre; Elp1LoxP/LoxP). Metabolite alterations correlated temporally with progressive RGC degeneration and were associated with reduced mitochondrial function, alterations in ATP production through the Cahill and mini-Krebs cycles, and phospholipid metabolism. Dopaminergic amacrine cell populations were reduced at timepoints P30–P90, and dopamine levels were 25–35% lower in CKO retinae compared to control retinae at P60. Overall, this study has expanded upon our current understanding of retina pathology in FD. This knowledge may apply to other retinal diseases that share hallmark features with FD and may help guide new avenues for novel non-invasive therapeutics to mitigate the progressive optic neuropathy in FD.
- Open Access
- 18 February 2024
- Published by MDPI AG in International Journal of Molecular Sciences
- Vol. 25 (4) , 2407
Primary Human M2 Macrophage Subtypes Are Distinguishable by Aqueous Metabolite Profiles
The complexity of macrophage (MΦ) plasticity and polarization states, which include classically activated pro-inflammatory (M1) and alternatively activated anti-inflammatory (M2) MΦ phenotypes, is becoming increasingly appreciated. Within the M2 MΦ polarization state, M2a, M2b, M2c, and M2d MΦ subcategories have been defined based on their expression of specific cell surface receptors, secreted cytokines, and specialized immune effector functions. The importance of immunometabolic networks in mediating the function and regulation of MΦ immune responses is also being increasingly recognized, although the exact mechanisms and extent of metabolic modulation of MΦ subtype phenotypes and functions remain incompletely understood. In this study, proton (1H) nuclear magnetic resonance (NMR) metabolomics was employed to determine the polar metabolomes of M2 MΦ subtypes and to investigate the relationship between aqueous metabolite profiles and M2 MΦ functional phenotypes. Results from this study demonstrate that M2a MΦs are most distinct from M2b, M2c, and M2d MΦ subtypes, and that M2b MΦs display several metabolic traits associated with an M1-like MΦ phenotype. The significance of metabolome differences for metabolites implicated in glycolysis, the tricarboxylic acid (TCA) cycle, phospholipid metabolism, and creatine–phosphocreatine cycling is discussed. Altogether, this study provides biochemical insights into the role of metabolism in mediating the specialized effector functions of distinct M2 MΦ subtypes and supports the concept of a continuum of macrophage activation states rather than two well-separated and functionally distinct M1/M2 MΦ classes, as originally proposed within a classical M1/M2 MΦ framework.
- 18 February 2024
- Published by MDPI AG in International Journal of Molecular Sciences
- Vol. 25 (4) , 2407
Open AccessPrimary Human M2 Macrophage Subtypes Are Distinguishable by Aqueous Metabolite Profiles
The complexity of macrophage (MΦ) plasticity and polarization states, which include classically activated pro-inflammatory (M1) and alternatively activated anti-inflammatory (M2) MΦ phenotypes, is becoming increasingly appreciated. Within the M2 MΦ polarization state, M2a, M2b, M2c, and M2d MΦ subcategories have been defined based on their expression of specific cell surface receptors, secreted cytokines, and specialized immune effector functions. The importance of immunometabolic networks in mediating the function and regulation of MΦ immune responses is also being increasingly recognized, although the exact mechanisms and extent of metabolic modulation of MΦ subtype phenotypes and functions remain incompletely understood. In this study, proton (1H) nuclear magnetic resonance (NMR) metabolomics was employed to determine the polar metabolomes of M2 MΦ subtypes and to investigate the relationship between aqueous metabolite profiles and M2 MΦ functional phenotypes. Results from this study demonstrate that M2a MΦs are most distinct from M2b, M2c, and M2d MΦ subtypes, and that M2b MΦs display several metabolic traits associated with an M1-like MΦ phenotype. The significance of metabolome differences for metabolites implicated in glycolysis, the tricarboxylic acid (TCA) cycle, phospholipid metabolism, and creatine–phosphocreatine cycling is discussed. Altogether, this study provides biochemical insights into the role of metabolism in mediating the specialized effector functions of distinct M2 MΦ subtypes and supports the concept of a continuum of macrophage activation states rather than two well-separated and functionally distinct M1/M2 MΦ classes, as originally proposed within a classical M1/M2 MΦ framework.
- Open Access
- 16 March 2023
- Published by MDPI AG in Metabolites
- Vol. 13 (3) , 433
A Comprehensive NMR Analysis of Serum and Fecal Metabolites in Familial Dysautonomia Patients Reveals Significant Metabolic Perturbations
Central metabolism has a profound impact on the clinical phenotypes and penetrance of neurological diseases such as Alzheimer’s (AD) and Parkinson’s (PD) diseases, Amyotrophic Lateral Sclerosis (ALS) and Autism Spectrum Disorder (ASD). In contrast to the multifactorial origin of these neurological diseases, neurodevelopmental impairment and neurodegeneration in Familial Dysautonomia (FD) results from a single point mutation in the ELP1 gene. FD patients represent a well-defined population who can help us better understand the cellular networks underlying neurodegeneration, and how disease traits are affected by metabolic dysfunction, which in turn may contribute to dysregulation of the gut–brain axis of FD. Here, 1H NMR spectroscopy was employed to characterize the serum and fecal metabolomes of FD patients, and to assess similarities and differences in the polar metabolite profiles between FD patients and healthy relative controls. Findings from this work revealed noteworthy metabolic alterations reflected in energy (ATP) production, mitochondrial function, amino acid and nucleotide catabolism, neurosignaling molecules, and gut-microbial metabolism. These results provide further evidence for a close interconnection between metabolism, neurodegeneration, and gut microbiome dysbiosis in FD, and create an opportunity to explore whether metabolic interventions targeting the gut–brain–metabolism axis of FD could be used to redress or slow down the progressive neurodegeneration observed in FD patients.
- 16 March 2023
- Published by MDPI AG in Metabolites
- Vol. 13 (3) , 433
Open AccessA Comprehensive NMR Analysis of Serum and Fecal Metabolites in Familial Dysautonomia Patients Reveals Significant Metabolic Perturbations
Central metabolism has a profound impact on the clinical phenotypes and penetrance of neurological diseases such as Alzheimer’s (AD) and Parkinson’s (PD) diseases, Amyotrophic Lateral Sclerosis (ALS) and Autism Spectrum Disorder (ASD). In contrast to the multifactorial origin of these neurological diseases, neurodevelopmental impairment and neurodegeneration in Familial Dysautonomia (FD) results from a single point mutation in the ELP1 gene. FD patients represent a well-defined population who can help us better understand the cellular networks underlying neurodegeneration, and how disease traits are affected by metabolic dysfunction, which in turn may contribute to dysregulation of the gut–brain axis of FD. Here, 1H NMR spectroscopy was employed to characterize the serum and fecal metabolomes of FD patients, and to assess similarities and differences in the polar metabolite profiles between FD patients and healthy relative controls. Findings from this work revealed noteworthy metabolic alterations reflected in energy (ATP) production, mitochondrial function, amino acid and nucleotide catabolism, neurosignaling molecules, and gut-microbial metabolism. These results provide further evidence for a close interconnection between metabolism, neurodegeneration, and gut microbiome dysbiosis in FD, and create an opportunity to explore whether metabolic interventions targeting the gut–brain–metabolism axis of FD could be used to redress or slow down the progressive neurodegeneration observed in FD patients.