Fitzgerald, C. | bioRxiv Science

bioRxiv2024

SpaMTP: Integrative Statistical Analysis and Visualisation of Spatial Metabolomics and Transcriptomics data.

The ability to spatially measure multi-modal data provides an unprecedented opportunity to comprehensively explore molecular regulation at transcriptional, translational and metabolic levels to acquire insights on cellular activities underpinning health and disease. However, there is currently a lack of analytical tools to integrate complementary information across different spatial-omics data modalities, particularly with respect to spatial metabolomics data, which is becoming increasingly invaluable. We introduce SpaMTP, a versatile software that implements an end-to-end integrative analysis of spatial metabolomics and transcriptomics data. Based in R, SpaMTP bridges processing functionalities for metabolomics data from Cardinal with user-friendly cell-centric analyses implemented in Seurat. Furthermore, SpaMTPs comprehensive analysis pipeline covers (1) automated mass-to-charge ratio (m/z) metabolite annotation; (2) a wide range of metabolite-gene based downstream statistical analyses including differential expression, pathway analysis, and correlation analysis; (3) integrative spatial-omics analysis; and (4) a suite of visualisation functions. For flexibility and interoperability, SpaMTP includes various functions for data import/export and object conversion, enabling seamless integration with other R and Python packages. We demonstrated the utility of SpaMTP to draw new biological understandings through analysing two biological system. We believe this software and implemented methods will be broadly utilised in spatial multi-omics and spatial metabolomics analyses.

bioinformatics↗

bioRxiv2019

Female lower urinary tract microbiota do not correspond to IC/PBS symptoms: a case-controlled study

ABSTRACTO_ST_ABSOBJECTIVEC_ST_ABSCurrent etiology of interstitial cystitis/painful bladder syndrome (IC/PBS) is poorly understood and multifactorial. Recent studies suggest the female urinary microbiota (FUM) contribute to IC/PBS symptoms. This study was designed to determine if the FUM, analyzed using mid-stream voided urine samples, differs between IC/PBS patients and controls.\n\nMATERIALS AND METHODSThis prospective case-controlled study compared the voided FUM of women with symptoms of urinary frequency, urgency, and bladder pain for greater than 6 months to the voided FUM of healthy female controls without pain. Bacterial identification was performed using 16S rRNA gene sequencing and EQUC, a validated enhanced urine culture approach. Urotype was defined by a genus present at >50% relative abundance. If no genus was present above this threshold, the urotype was classified as mixe. Chi-square and Fishers exact tests were performed. P-values <0.05 were considered significant.\n\nRESULTSA mid-stream voided specimen was collected from 21 IC/PBS patients and 20 asymptomatic controls. Both groups had similar demographics. Urotypes did not differ between cohorts as assessed by either EQUC or 16S rRNA gene sequencing. We detected no significant differences between cohorts in terms of alpha-diversity. Cohorts also were not distinct using Principle Component Analysis or hierarchical clustering. Detection by EQUC of bacterial species considered uropathogenic was high in both cohorts, but detection of these uropathogenic species did not differ between groups (p=0.10).\n\nCONCLUSIONSEnhanced culture and modern DNA sequencing methods provide evidence that IC/PBS symptoms may not be related to differences in the FUM, at least not its bacterial components. Future larger studies are needed to confirm this preliminary finding.

microbiology↗