SUPPRESION OF MITOCHONDRIAL RESPIRATION IS A FEATURE OF CELLULAR GLUCOSE TOXICITY.

Glucose toxicity is central to the myriad complications of diabetes and is now believed to encompass neurodegenerative diseases and cancer as well as microvascular and macrovascular disease. Due to the widespread benefits of SGLT2 inhibitors, which affect glucose uptake in the kidney proximal tubular cell, a focus on cell metabolism in response to glucose has important implications for overall health. We previously found that a -Warburg-type effect underlies diabetic kidney disease and involves metabolic reprogramming. This is now supported by quantitative measurements of superoxide measurement in the diabetic kidney and systems biology analysis of urine metabolites in patients. Further exploration of mechanisms underlying mediators of mitochondrial suppression will be critical in understanding the chronology of glucose-induced toxicity and developing new therapeutics to arrest the systemic glucose toxicity of diabetes.

A multimodal and integrated approach to interrogate human kidney biopsies with rigor and reproducibility: guidelines from the Kidney Precision Medicine Project.

Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate three-dimensional (3-D) molecular atlases of healthy and diseased kidney biopsies by using multiple state-of-the-art omics and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single-cell level or in 3-D space is a significant challenge that can be a futile exercise if not well controlled. We describe a "follow the tissue" pipeline for generating a reliable and authentic single-cell/region 3-D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation, and harmonization across different omics and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis, and sharing. We established benchmarks for quality control, rigor, reproducibility, and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before their being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multiomics and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.

Restoring mitochondrial superoxide levels with elamipretide (MTP-131) protects db/db mice against progression of diabetic kidney disease.

Exposure to chronic hyperglycemia because of diabetes mellitus can lead to development and progression of diabetic kidney disease (DKD). We recently reported that reduced superoxide production is associated with mitochondrial dysfunction in the kidneys of mouse models of type 1 DKD. We also demonstrated that humans with DKD have significantly reduced levels of mitochondrion-derived metabolites in their urine. Here we examined renal superoxide production in a type 2 diabetes animal model, the db/db mouse, and the role of a mitochondrial protectant, MTP-131 (also called elamipretide, SS-31, or Bendavia) in restoring renal superoxide production and ameliorating DKD. We found that 18-week-old db/db mice have reduced renal and cardiac superoxide levels, as measured by dihydroethidium oxidation, and increased levels of albuminuria, mesangial matrix accumulation, and urinary H2O2 Administration of MTP-131 significantly inhibited increases in albuminuria, urinary H2O2, and mesangial matrix accumulation in db/db mice and fully preserved levels of renal superoxide production in these mice. MTP-131 also reduced total renal lysocardiolipin and major lysocardiolipin subspecies and preserved lysocardiolipin acyltransferase 1 expression in db/db mice. These results indicate that, in type 2 diabetes, DKD is associated with reduced renal and cardiac superoxide levels and that MTP-131 protects against DKD and preserves physiological superoxide levels, possibly by regulating cardiolipin remodeling.

Serum metabolomics identifies metabolite panels that differentiate lame dairy cows from healthy ones.

INTRODUCTION: Although much is known about lameness application of metabolomics technologies to better understanding its etiology and pathogenesis is of utmost interest. OBJECTIVES: The objective of this study was to investigate serum metabolite alterations in pre-lame, lame and post-lame dairy cows in order to identify potential screening serum metabolite biomarkers for lameness and better understand its pathobiology. METHODS: A combination of direct injection and tandem mass spectrometry (DI-MS/MS) with a reverse-phase liquid chromatography and tandem mass spectrometry (LC-MS/MS) analysis was performed in the serum of six cases of lameness and 20 healthy control cows (CON) at - 8 and - 4 weeks prepartum, at lameness diagnosis week, and at + 4 and + 8 weeks postpartum. RESULTS: Data indicated that pre-lame, lame, and post-lame cows experienced altered concentrations of multiple metabolites. It is interesting to note that throughout the 16-weeks of the study, 7 serum metabolites [e.g., diacyl-phosphatidylcholine (PC aa) C30:0, phosphatidylcholine acyl-alkyl (PC ae) C40:2, sphingomyelin (SM) (OH) C14:1, SM C18:0, isoleucine (Ile), leucine (Leu), and lysine (Lys)] differentiated CON cows from the lame ones. Furthermore, 4 metabolic pathways (i.e., Lys degradation, biotin metabolism, tryptophan (Trp) metabolism, and valine [(Val)-Leu-Ile degradation) were altered in cows with lameness during the onset and progression of the disease. CONCLUSION: Multiple metabolite and pathway alterations were identified in the serum of pre-lame, lame, and post-lame cows that through light into the pathobiology of the disease and that can be used as potential biomarker sets that can predict the risk of lameness in dairy cows.

DESI-MSI and METASPACE indicates lipid abnormalities and altered mitochondrial membrane components in diabetic renal proximal tubules.

INTRODUCTION: Diabetic kidney disease (DKD) is the most prevalent complication in diabetic patients, which contributes to high morbidity and mortality. Urine and plasma metabolomics studies have been demonstrated to provide valuable insights for DKD. However, limited information on spatial distributions of metabolites in kidney tissues have been reported. OBJECTIVES: In this work, we employed an ambient desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) coupled to a novel bioinformatics platform (METASPACE) to characterize the metabolome in a mouse model of DKD. METHODS: DESI-MSI was performed for spatial untargeted metabolomics analysis in kidneys of mouse models (F1 C57BL/6J-Ins2Akita male mice at 17 weeks of age) of type 1 diabetes (T1D, n = 5) and heathy controls (n = 6). RESULTS: Multivariate analyses (i.e., PCA and PLS-DA (a 2000 permutation test: P < 0.001)) showed clearly separated clusters for the two groups of mice on the basis of 878 measured m/z's in kidney cortical tissues. Specifically, mice with T1D had increased relative abundances of pseudouridine, accumulation of free polyunsaturated fatty acids (PUFAs), and decreased relative abundances of cardiolipins in cortical proximal tubules when compared with healthy controls. CONCLUSION: Results from the current study support potential key roles of pseudouridine and cardiolipins for maintaining normal RNA structure and normal mitochondrial function, respectively, in cortical proximal tubules with DKD. DESI-MSI technology coupled with METASPACE could serve as powerful new tools to provide insight on fundamental pathways in DKD.

GC-MS Metabolomics Identifies Metabolite Alterations That Precede Subclinical Mastitis in the Blood of Transition Dairy Cows.

The objectives of this study were to determine alterations in the serum metabolites related to amino acid (AA), carbohydrate, and lipid metabolism in transition dairy cows before diagnosis of subclinical mastitis (SCM), during, and after diagnosis of disease. A subclinical mastitis case was determined as a cow having somatic cell count (SCC) > 200 000/mL of milk for two or more consecutive reports. Blood samples were collected from 100 Holstein dairy cows at five time points at -8 and -4 weeks before parturition, at the week of SCM diagnosis, and +4 and +8 weeks after parturition. Twenty healthy control cows (CON) and six cows that were diagnosed with SCM were selected for serum analysis with GC-MS. At -8 weeks a total of 13 metabolites were significantly altered in SCM cows. In addition, at the week of SCM diagnosis 17 metabolites were altered in these cows. Four weeks after parturition 10 metabolites were altered in SCM cows and at +8 weeks 11 metabolites were found to be different between the two groups. Valine (Val), serine (Ser), tyrosine (Tyr), and phenylalanine (Phe) had very good predictive abilities for SCM and could be used at -8 weeks and -4 weeks before calving. Combination of Val, isoleucine (Ile), Ser, and proline (Pro) can be used as diagnostic biomarkers of SCM during early stages of lactation at +4 to +8 weeks after parturition. In conclusion, SCM is preceded and followed by alteration in AA metabolism.

A metabolite-GWAS (mGWAS) approach to unveil chronic kidney disease progression.

In this issue, McMahon et al. report that, by combining phenotypic, metabolomic, and genetic data, they could better detect chronic kidney disease at the early stages and provide insight into its pathobiology. The most significant findings of the study are that several urinary metabolites (e.g., glycine and histidine) were identified as early risk factors for chronic kidney disease, and metabolites with genomewide association study analysis identified associations of urinary metabolites (i.e., lysine and NG-monomethyl-l-arginine) with single-nucleotide polymorphisms of SLC7A9.

Metabolomic fingerprinting of milk fever cows: Pre- and postpartum metabolite alterations.

BACKGROUND: Milk fever (MF), a metabolic disorder in dairy cows characterized by low blood calcium concentrations postpartum, is well-recognized clinically. However, comprehensive data on the alteration of metabolites associated with this condition remains sparse. HYPOTHESIS: Delineate serum metabolite profiles and metabolic pathways preceding, coinciding with, and after the onset of MF. ANIMALS: Twenty-six cows, including 20 healthy cows and 6 cows initially affected by MF. Because of culling, the number of MF-affected cows decreased to 4 at MF week, +4 weeks, and +8 weeks postpartum. METHODS: A nested case-control longitudinal study was conducted, with blood samples collected at -8 and -4 weeks prepartum, MF week, and +4 and +8 weeks postpartum. Serum analysis utilized direct injection/liquid chromatography/tandem mass spectrometry (DI/LC/MS/MS) techniques. RESULTS: Key findings included the identification of diverse metabolites such as hexose, amino acids, phosphatidylcholines, lysophosphatidylcholines, and sphingomyelin, which varied between studied groups (P < .05). The most marked metabolic alterations were observed 4 weeks prepartum. In total, 42, 56, 38, 29, and 24 metabolites distinguished the MF group at the respective time points (P < .05). Additionally, 33 metabolic pathways, including amino acid, antioxidant metabolism, fatty acid degradation, and carbohydrate processing, were impacted (P < .05). CONCLUSIONS AND CLINICAL IMPORTANCE: Metabolic disruptions in dairy cows begin several weeks before the clinical manifestation of MF and persist up to 8 weeks postpartum. These findings emphasize the complexity of MF, extending beyond only hypocalcemia and indicate the necessity for preemptive monitoring in dairy herd management.

Quinolinic acid links kidney injury to brain toxicity.

Kidney dysfunction often leads to neurological impairment, yet the complex kidney-brain relationship remains elusive. We employed spatial and bulk metabolomics to investigate a mouse model of rapid kidney failure induced by mouse double minute 2 ( Mdm2) conditional deletion in the kidney tubules to interrogate kidney and brain metabolism. Pathway enrichment analysis of focused plasma metabolomics panel pinpointed tryptophan metabolism as the most altered pathway with kidney failure. Spatial metabolomics showed toxic tryptophan metabolites in the kidneys and brains, revealing a novel connection between advanced kidney disease and accelerated kynurenine degradation. In particular, the excitotoxic metabolite quinolinic acid was localized in ependymal cells adjacent to the ventricle in the setting of kidney failure. These findings were associated with brain inflammation and cell death. A separate mouse model of acute kidney injury also had an increase in circulating toxic tryptophan metabolites along with altered brain inflammation. Patients with advanced CKD similarly demonstrated elevated plasma kynurenine metabolites and quinolinic acid was uniquely correlated with fatigue and reduced quality of life in humans. Overall, our study identifies the kynurenine pathway as a bridge between kidney decline, systemic inflammation, and brain toxicity, offering potential avenues for diagnosis and treatment of neurological issues in kidney disease.

Glycolytic lactate in diabetic kidney disease.

Lactate elevation is a well-characterized biomarker of mitochondrial dysfunction, but its role in diabetic kidney disease (DKD) is not well defined. Urine lactate was measured in patients with type 2 diabetes (T2D) in 3 cohorts (HUNT3, SMART2D, CRIC). Urine and plasma lactate were measured during euglycemic and hyperglycemic clamps in participants with type 1 diabetes (T1D). Patients in the HUNT3 cohort with DKD had elevated urine lactate levels compared with age- and sex-matched controls. In patients in the SMART2D and CRIC cohorts, the third tertile of urine lactate/creatinine was associated with more rapid estimated glomerular filtration rate decline, relative to first tertile. Patients with T1D demonstrated a strong association between glucose and lactate in both plasma and urine. Glucose-stimulated lactate likely derives in part from proximal tubular cells, since lactate production was attenuated with sodium-glucose cotransporter-2 (SGLT2) inhibition in kidney sections and in SGLT2-deficient mice. Several glycolytic genes were elevated in human diabetic proximal tubules. Lactate levels above 2.5 mM potently inhibited mitochondrial oxidative phosphorylation in human proximal tubule (HK2) cells. We conclude that increased lactate production under diabetic conditions can contribute to mitochondrial dysfunction and become a feed-forward component to DKD pathogenesis.

Attenuated kidney oxidative metabolism in young adults with type 1 diabetes.

BACKGROUND: In type 1 diabetes (T1D), impaired insulin sensitivity may contribute to the development of diabetic kidney disease (DKD) through alterations in kidney oxidative metabolism. METHODS: Young adults with T1D (n = 30) and healthy controls (HC, n = 20) underwent hyperinsulinemic-euglycemic clamp studies, MRI, 11C-acetate PET, kidney biopsies, single-cell RNA sequencing, and spatial metabolomics to assess this relationship. RESULTS: Participants with T1D had significantly higher glomerular basement membrane thickness compared to HC. T1D participants exhibited lower insulin sensitivity and cortical oxidative metabolism, correlating with higher insulin sensitivity. Proximal tubular transcripts of TCA cycle and oxidative phosphorylation enzymes were lower in T1D. Spatial metabolomics showed reductions in tubular TCA cycle intermediates, indicating mitochondrial dysfunction. The Slingshot algorithm identified a lineage of proximal tubular cells progressing from stable to adaptive/maladaptive subtypes, using pseudotime trajectory analysis, which computationally orders cells along a continuum of states. This analysis revealed distinct distribution patterns between T1D and HC, with attenuated oxidative metabolism in T1D attributed to a greater proportion of adaptive/maladaptive subtypes with low expression of TCA cycle and oxidative phosphorylation transcripts. Pseudotime progression associated with higher HbA1c, BMI, GBM, and lower insulin sensitivity and cortical oxidative metabolism. CONCLUSION: These early structural and metabolic changes in T1D kidneys may precede clinical DKD. CLINICALTRIALS: gov NCT04074668.

Role of endogenous adenine in kidney failure and mortality with diabetes.

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality, however, few mechanistic biomarkers are available for high risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from Chronic Renal Insufficiency Cohort (CRIC), Singapore Study of Macro-Angiopathy and Reactivity in Type 2 Diabetes (SMART2D), and the Pima Indian Study determined if urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in CRIC (HR 1.57, 1.18, 2.10) and SMART2D (HR 1.77, 1.00, 3.12). ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in CRIC (HR 2.36, 1.26, 4.39), SMART2D (HR 2.39, 1.08, 5.29), and Pima Indian study (HR 4.57, CI 1.37-13.34). Empagliflozin lowered UAdCR in non-macroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology and transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mammalian target of rapamycin (mTOR). Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.

Endogenous adenine mediates kidney injury in diabetic models and predicts diabetic kidney disease in patients.

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality; however, few mechanistic biomarkers are available for high-risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from the Chronic Renal Insufficiency Cohort (CRIC) study, the Singapore Study of Macro-angiopathy and Micro-vascular Reactivity in Type 2 Diabetes (SMART2D), and the American Indian Study determined whether urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in the CRIC study and SMART2D. ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in the CRIC study, SMART2D, and the American Indian study. Empagliflozin lowered UAdCR in nonmacroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology, and single-cell transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mTOR. Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.

Identification of Serum-Predictive Biomarkers for Subclinical Mastitis in Dairy Cows and New Insights into the Pathobiology of the Disease.

Targeted direct injection/liquid chromatography coupled to tandem mass spectrometry-based metabolomics was employed to identify metabolite alterations that could differentiate subclinical mastitis (SCM) from control (CON) dairy cows at -8, -4, disease diagnosis, +4 and +8 wks relative to parturition. We identified and measured 128 metabolites in the serum. Univariate analysis revealed significant alterations of serum metabolites at all five time points studied. By applying multivariate analyses including principle component analysis and partial least squares-discriminant analysis, some of the metabolites were found to have the strongest power for discriminating the SCM from CON cows. The top five metabolites with the greatest variable importance in projection values were selected as potential biomarkers for SCM. A set of five serum metabolites including lysine, ornithine, isoleucine, LysoPC a C17:0, and leucine at -8 wks and five other metabolites including lysine, leucine, isoleucine, kynurenine, and sphingomyelin (SM) C26:0 at -4 wks prepartum were determined as predictive biomarkers for SCM, which provided highly predictive capabilities with AUC (area under the curve) at 1.00. Five metabolites including lysine, leucine, isoleucine, kynurenine, and SM C26:1 in the serum were identified as diagnostic biomarkers for SCM with the AUC of 1.00. Moreover, we observed that distinct metabolic pathways were affected in SCM cows including lysine degradation, biotin, cysteine, methionine, and glutathione metabolism, valine, leucine, and isoleucine biosynthesis and degradation, and aminoacyl-tRNA biosynthesis prior to and during the occurrence of the disease. Results of this study showed that metabolomics analyses can be used to identify susceptible cows to SCM starting from -8 and -4 wks prepartum and that blood can be used to diagnose cows with SCM.

A dataset of distribution of antibiotic occurrence in solid environmental matrices in China.

While there is growing global concern about the impact of antibiotic residues on emergence and enhancement bacteria's resistance, toxicity to natural organisms, and, ultimately, public health, a concise picture of measured environmental concentrations of antibiotic occurrence in multiple environmental matrices, particularly in solid matrices (e.g., sludge, soil, and sediments) is still elusive, especially for China. In this paper, we present an up-to-date dataset of the distribution of antibiotic occurrence in solid environmental matrices in China, derived from 210 peer-reviewed literature published between 2000 and 2020. We extracted geographical sampling locations and measured concentration associated with antibiotic occurrence reported in English and Chinese original publications, and applied quality-control procedures to remove duplicates and ensure accuracy. The dataset contains 6929 records of geo-referenced occurrences for 135 antibiotics distributed over 391 locations distinguished at four levels of scale i.e., provincial, prefectural, county, and township or finer. The geographical dataset provides an updated map of antibiotic occurrence in solid environmental matrices in China and can be used for further environmental health risk assessment.

A reference tissue atlas for the human kidney.

Kidney Precision Medicine Project (KPMP) is building a spatially specified human kidney tissue atlas in health and disease with single-cell resolution. Here, we describe the construction of an integrated reference map of cells, pathways, and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 56 adult subjects. We use single-cell/nucleus transcriptomics, subsegmental laser microdissection transcriptomics and proteomics, near-single-cell proteomics, 3D and CODEX imaging, and spatial metabolomics to hierarchically identify genes, pathways, and cells. Integrated data from these different technologies coherently identify cell types/subtypes within different nephron segments and the interstitium. These profiles describe cell-level functional organization of the kidney following its physiological functions and link cell subtypes to genes, proteins, metabolites, and pathways. They further show that messenger RNA levels along the nephron are congruent with the subsegmental physiological activity. This reference atlas provides a framework for the classification of kidney disease when multiple molecular mechanisms underlie convergent clinical phenotypes.

A Multi-Platform Metabolomics Approach Identifies Urinary Metabolite Signatures That Differentiate Ketotic From Healthy Dairy Cows.

Ketosis and subclinical ketosis are widespread among dairy cows especially after calving. Etiopathology of ketosis has been related to negative energy balance. The objective of this study was to investigate metabolite fingerprints in the urine of pre-ketotic, ketotic, and post-ketotic cows to identify potential metabolite alterations that can be used in the future to identify susceptible cows for ketosis and metabolic pathways involved in the development of disease. In this study, NMR, DI/LC-MS/MS, and GC-MS-based metabolomics were used to analyze urine samples from 6 cows diagnosed with ketosis and 20 healthy control (CON) cows at -8 and -4 weeks prepartum, the week (+1 to +3) of ketosis diagnosis, and at +4 and +8 weeks after parturition. Univariate and multivariate analyses were used to screen metabolite panels that can identify cows at their pre-ketotic stage. A total of 54, 42, 48, 16, and 31 differential metabolites between the ketotic and CON cows were identified at -8 and -4 weeks prepartum, ketosis week, and at +4, and +8 weeks postpartum, respectively. Variable importance in projection (VIP) plots ranked the most significant differential metabolites, which differentiated ketotic cows from the CON ones. Additionally, several metabolic pathways that are related to ketosis were identified. Moreover, two promising metabolite panels were identified which clearly separated ketotic from CON cows with excellent level of sensitivity and specificity. Overall, multiple urinary metabolite alterations were identified in pre-ketotic, ketotic, and post-ketotic cows. The metabolite panels identified need to be validated in the future in a larger cohort of animals.

A Targeted Serum Metabolomics GC-MS Approach Identifies Predictive Blood Biomarkers for Retained Placenta in Holstein Dairy Cows.

The retained placenta is a common pathology of dairy cows. It is associated with a significant drop in the dry matter intake, milk yield, and increased susceptibility of dairy cows to metritis, mastitis, and displaced abomasum. The objective of this study was to identify metabolic alterations that precede and are associated with the disease occurrence. Blood samples were collected from 100 dairy cows at -8 and -4 weeks prior to parturition and on the day of retained placenta, and only 16 healthy cows and 6 cows affected by retained placenta were selected to measure serum polar metabolites by a targeted gas chromatography-mass spectroscopy (GC-MS) metabolomics approach. A total of 27 metabolites were identified and quantified in the serum. There were 10, 18, and 17 metabolites identified as being significantly altered during the three time periods studied. However, only nine metabolites were identified as being shared among the three time periods including five amino acids (Asp, Glu, Ser, Thr, and Tyr), one sugar (myo-inositol), phosphoric acid, and urea. The identified metabolites can be used as predictive biomarkers for the risk of retained placenta in dairy cows and might help explain the metabolic processes that occur prior to the incidence of the disease and throw light on the pathomechanisms of the disease.

Assessing the role of high-speed rail in shaping the spatial patterns of urban and rural development: A case of the Middle Reaches of the Yangtze River, China.

China has experienced rapid residential land expansion in both urban and rural areas over the past three decades, causing complex ecological and environmental challenges. Much research attention has been paid on urbanisation, yet little is known about rural development. In this study, we analysed and compared the changes in a selected number of landscape indices describing the spatial patterns of both urban and rural area in the Middle Reaches of the Yangtze River in central China from 2005 to 2015 and explored how these changes could be associated with the development of high-speed rail (HSR) using spatial error models. We found a partial synchronised spatial development pattern between urban and rural areas in central China, with an increasingly fragmented pattern for both urban and rural areas, albeit rural areas were expanded in a less contiguous but more complex and dispersed fashion. The impacts of the provision of HSR services on the region's spatial development were found to be multi-level. It was associated with greater urban expansion and dispersion at the county/district level and amplified rural patch size and complexity at the patch level. The departure frequency of HSR trains and proximity to HSR station were found to have affected the magnitude of the impact of HSR service provision on regional spatial development. Our results shed lights on the spatio-temporal evolution of an ecologically important region, add new evidence into the expanding fields of urban and rural morphological studies in China, and provide valuable decision support information for integrated spatial planning of transportation and land use.