Wimal Pathmasiri

Antibiotic-mediated gut microbiome perturbation accelerates development of type 1 diabetes in mice.

The early life microbiome plays important roles in host immunological and metabolic development. Because the incidence of type 1 diabetes (T1D) has been increasing substantially in recent decades, we hypothesized that early-life antibiotic use alters gut microbiota, which predisposes to disease. Using non-obese diabetic mice that are genetically susceptible to T1D, we examined the effects of exposure to either continuous low-dose antibiotics or pulsed therapeutic antibiotics (PAT) early in life, mimicking childhood exposures. We found that in mice receiving PAT, T1D incidence was significantly higher, and microbial community composition and structure differed compared with controls. In pre-diabetic male PAT mice, the intestinal lamina propria had lower Th17 and Treg proportions and intestinal SAA expression than in controls, suggesting key roles in transducing the altered microbiota signals. PAT affected microbial lipid metabolism and host cholesterol biosynthetic gene expression. These findings show that early-life antibiotic treatments alter the gut microbiota and its metabolic capacities, intestinal gene expression and T-cell populations, accelerating T1D onset in non-obese diabetic mice.

Flanking Bases Influence the Nature of DNA Distortion by Platinum 1,2-Intrastrand (GG) Cross-Links

The differences in efficacy and molecular mechanisms of platinum anti-cancer drugs cisplatin (CP) and oxaliplatin (OX) are thought to be partially due to the differences in the DNA conformations of the CP and OX adducts that form on adjacent guanines on DNA, which in turn influence the binding of damage-recognition proteins that control downstream effects of the adducts. Here we report a comprehensive comparison of the structural distortion of DNA caused by CP and OX adducts in the TGGT sequence context using nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics (MD) simulations. When compared to our previous studies in other sequence contexts, these structural studies help us understand the effect of the sequence context on the conformation of Pt-GG DNA adducts. We find that both the sequence context and the type of Pt-GG DNA adduct (CP vs. OX) play an important role in the conformation and the conformational dynamics of Pt-DNA adducts, possibly explaining their influence on the ability of many damage-recognition proteins to bind to Pt-DNA adducts.

Metabolomics Analysis of Hormone-Responsive and Triple-Negative Breast Cancer Cell Responses to Paclitaxel Identify Key Metabolic Differences

To date, no targeted therapies are available to treat triple negative breast cancer (TNBC), while other breast cancer subtypes are responsive to current therapeutic treatment. Metabolomics was conducted to reveal differences in two hormone receptor-negative TNBC cell lines and two hormone receptor-positive Luminal A cell lines. Studies were conducted in the presence and absence of paclitaxel (Taxol). TNBC cell lines had higher levels of amino acids, branched-chain amino acids, nucleotides, and nucleotide sugars and lower levels of proliferation-related metabolites like choline compared with Luminal A cell lines. In the presence of paclitaxel, each cell line showed unique metabolic responses, with some similarities by type. For example, in the Luminal A cell lines, levels of lactate and creatine decreased while certain choline metabolites and myo-inositol increased with paclitaxel. In the TNBC cell lines levels of glutamine, glutamate, and glutathione increased, whereas lysine, proline, and valine decreased in the presence of drug. Profiling secreted inflammatory cytokines in the conditioned media demonstrated a greater response to paclitaxel in the hormone-positive Luminal cells compared with a secretion profile that suggested greater drug resistance in the TNBC cells. The most significant differences distinguishing the cell types based on pathway enrichment analyses were related to amino acid, lipid and carbohydrate metabolism pathways, whereas several biological pathways were differentiated between the cell lines following treatment.

A General Method for Targeted Quantitative Cross-Linking Mass Spectrometry.

Chemical cross-linking mass spectrometry (XL-MS) provides protein structural information by identifying covalently linked proximal amino acid residues on protein surfaces. The information gained by this technique is complementary to other structural biology methods such as x-ray crystallography, NMR and cryo-electron microscopy[1]. The extension of traditional quantitative proteomics methods with chemical cross-linking can provide information on the structural dynamics of protein structures and protein complexes. The identification and quantitation of cross-linked peptides remains challenging for the general community, requiring specialized expertise ultimately limiting more widespread adoption of the technique. We describe a general method for targeted quantitative mass spectrometric analysis of cross-linked peptide pairs. We report the adaptation of the widely used, open source software package Skyline, for the analysis of quantitative XL-MS data as a means for data analysis and sharing of methods. We demonstrate the utility and robustness of the method with a cross-laboratory study and present data that is supported by and validates previously published data on quantified cross-linked peptide pairs. This advance provides an easy to use resource so that any lab with access to a LC-MS system capable of performing targeted quantitative analysis can quickly and accurately measure dynamic changes in protein structure and protein interactions.

Preterm neonatal urinary renal developmental and acute kidney injury metabolomic profiling: An exploratory study

BackgroundAcute kidney injury (AKI) staging has been developed in the adult and pediatric populations, but these do not yet exist for the neonatal population. Metabolomics was utilized to uncover biomarkers of normal and AKI-associated renal function in preterm infants. The study comprised 20 preterm infants with an AKI diagnosis who were matched by gestational age and gender to 20 infants without an AKI diagnosis.MethodsUrine samples from pre-term newborn infants collected on day 2 of life were analyzed using broad-spectrum nuclear magnetic resonance (NMR) metabolomics. Multivariate analysis methods were used to identify metabolite profiles that differentiated AKI and no AKI, and to identify a metabolomics profile correlating with gestational age in infants with and without AKI.ResultsThere was a clear distinction between the AKI and no-AKI profiles. Two previously identified biomarkers of AKI, hippurate and homovanillate, differentiated AKI from no-AKI profiles. Pathway analysis revealed similarities to cholinergic neurons, prenatal nicotine exposure on pancreatic β cells, and amitraz-induced inhibition of insulin secretion. Additionally, a pH difference was noted. Both pH and the metabolites were found to be associated with AKI; however, only the metabotype was a significant predictor of AKI. Pathways for the no-AKI group that correlated uniquely with gestational age included aminoacyl-t-RNA biosynthesis, whereas pathways in the AKI group yielded potential metabolite changes in pyruvate metabolism.ConclusionsMetabolomics was able to differentiate the urinary profiles of neonates with and without an AKI diagnosis and metabolic developmental profiles correlated with gestational age. Further studies in larger cohorts are needed to validate these results.

Pretreatment with indomethacin results in increased heat stroke severity during recovery in a rodent model of heat stroke

It has been suggested that medications can increase heat stroke (HS) susceptibility/severity. We investigated whether the nonsteroidal anti-inflammatory drug (NSAID) indomethacin (INDO) increases HS severity in a rodent model. Core temperature (Tc) of male, C57BL/6J mice (n = 45) was monitored continuously, and mice were given a dose of INDO [low dose (LO) 1 mg/kg or high dose (HI) 5 mg/kg in flavored treat] or vehicle (flavored treat) before heating. HS animals were heated to 42.4°C and euthanized at three time points for histological, molecular, and metabolic analysis: onset of HS [maximal core temperature (Tc,Max)], 3 h of recovery [minimal core temperature or hypothermia depth (HYPO)], and 24 h of recovery (24 h). Nonheated (control) animals underwent identical treatment in the absence of heat. INDO (LO or HI) had no effect on physiological indicators of performance (e.g., time to Tc,Max, thermal area, or cooling time) during heating or recovery. HI INDO resulted in 45% mortality rate by 24 h (HI INDO + HS group). The gut showed dramatic increases in gross morphological hemorrhage in HI INDO + HS in both survivors and nonsurvivors. HI INDO + HS survivors had significantly lower red blood cell counts and hematocrit suggesting significant hemorrhage. In the liver, HS induced cell death at HYPO and increased inflammation at Tc,Max, HYPO, and 24 h; however, there was additional effect with INDO + HS group. Furthermore, the metabolic profile of the liver was disturbed by heat, but there was no additive effect of INDO + HS. This suggests that there is an increase in morbidity risk with INDO + HS, likely resulting from significant gut injury.NEW & NOTEWORTHY This paper suggests that in a translational mouse model, NSAIDs may be counterindicated in situations that put an individual at risk of heat injury. We show here that a small, single dose of the NSAID indomethacin before heat stroke has a dramatic and highly damaging effect on the gut, which ultimately leads to increased systemic morbidity.

A Microbiomic Analysis in African Americans with Colonic Lesions Reveals Streptococcus sp.VT162 as a Marker of Neoplastic Transformation

Increasing evidence suggests a role of the gut microbiota in colorectal carcinogenesis (CRC). To detect bacterial markers of colorectal cancer in African Americans a metabolomic analysis was performed on fecal water extracts. DNA from stool samples of adenoma and healthy subjects and from colon cancer and matched normal tissues was analyzed to determine the microbiota composition (using 16S rDNA) and genomic content (metagenomics). Metagenomic functions with discriminative power between healthy and neoplastic specimens were established. Quantitative Polymerase Chain Reaction (q-PCR) using primers and probes specific to Streptococcus sp. VT_162 were used to validate this bacterium association with neoplastic transformation in stool samples from two independent cohorts of African Americans and Chinese patients with colorectal lesions. The metabolomic analysis of adenomas revealed low amino acids content. The microbiota in both cancer vs. normal tissues and adenoma vs. normal stool samples were different at the 16S rRNA gene level. Cross-mapping of metagenomic data led to 9 markers with significant discriminative power between normal and diseased specimens. These markers identified with Streptococcus sp. VT_162. Q-PCR data showed a statistically significant presence of this bacterium in advanced adenoma and cancer samples in an independent cohort of CRC patients. We defined metagenomic functions from Streptococcus sp. VT_162 with discriminative power among cancers vs. matched normal and adenomas vs. healthy subjects’ stools. Streptococcus sp. VT_162 specific 16S rDNA was validated in an independent cohort. These findings might facilitate non-invasive screening for colorectal cancer.

Antibiotic-induced acceleration of type 1 diabetes alters maturation of innate intestinal immunity

The early-life intestinal microbiota plays a key role in shaping host immune system development. We found that a single early-life antibiotic course (1PAT) accelerated type 1 diabetes (T1D) development in male NOD mice. The single course had deep and persistent effects on the intestinal microbiome, leading to altered cecal, hepatic, and serum metabolites. The exposure elicited sex-specific effects on chromatin states in the ileum and liver and perturbed ileal gene expression, altering normal maturational patterns. The global signature changes included specific genes controlling both innate and adaptive immunity. Microbiome analysis revealed four taxa each that potentially protect against or accelerate T1D onset, that were linked in a network model to specific differences in ileal gene expression. This simplified animal model reveals multiple potential pathways to understand pathogenesis by which early-life gut microbiome perturbations alter a global suite of intestinal responses, contributing to the accelerated and enhanced T1D development.

Correlated metabolomic, genomic, and histologic phenotypes in histologically normal breast tissue

Breast carcinogenesis is a multistep process accompanied by widespread molecular and genomic alterations, both in tumor and in surrounding microenvironment. It is known that tumors have altered metabolism, but the metabolic changes in normal or cancer-adjacent, nonmalignant normal tissues and how these changes relate to alterations in gene expression and histological composition are not well understood. Normal or cancer-adjacent normal breast tissues from 99 women of the Normal Breast Study (NBS) were evaluated. Data of metabolomics, gene expression and histological composition was collected by mass spectrometry, whole genome microarray, and digital image, respectively. Unsupervised clustering analysis determined metabolomics-derived subtypes. Their association with genomic and histological features, as well as other breast cancer risk factors, genomic and histological features were evaluated using logistic regression. Unsupervised clustering of metabolites resulted in two main clusters. The metabolite differences between the two clusters suggested enrichment of pathways involved in lipid metabolism, cell growth and proliferation, and migration. Compared with Cluster 1, subjects in Cluster 2 were more likely to be obese (body mass index ≥30 kg/m2, p<0.05), have increased adipose proportion (p<0.01) and associated with a previously defined Active genomic subtype (p<0.01). By the integrated analyses of histological, metabolomics and transcriptional data, we characterized two distinct subtypes of non-malignant breast tissue. Further research is needed to validate our findings, and understand the potential role of these alternations in breast cancer initiation, progression and recurrence.

Stable Isotope-Resolved Metabolomic Differences between Hormone-Responsive and Triple-Negative Breast Cancer Cell Lines

Purpose To conduct an exploratory study to identify mechanisms that differentiate Luminal A (BT474 and MCF-7) and triple-negative (MDA-MB-231 and MDA-MB-468) breast cancer (BCa) cell lines to potentially provide novel therapeutic targets based on differences in energy utilization. Methods Cells were cultured in media containing either [U-13C]-glucose or [U-13C]-glutamine for 48 hours. Conditioned media and cellular extracts were analyzed by 1H and 13C NMR spectroscopy. Results MCF-7 cells consumed the most glucose, producing the most lactate, demonstrating the greatest Warburg effect-associated energy utilization. BT474 cells had the highest tricarboxylic acid cycle (TCA) activity. The majority of energy utilization patterns in MCF-7 cells were more similar to MDA-MB-468 cells, while the patterns for BT474 cells were more similar to MDA-MB-231 cells. Compared to the Luminal A cell lines, TNBC cell lines consumed more glutamine and less glucose. BT474 and MDA-MB-468 cells produced high amounts of 13C-glycine from media [U-13C]-glucose which was integrated into glutathione, indicating de novo synthesis. Conclusions Stable isotopic resolved metabolomics using 13C substrates provided mechanistic information about energy utilization that was difficult to interpret using 1H data alone. Overall, cell lines that have different hormone receptor status have different energy utilization requirements, even if they are classified by the same clinical BCa subtype; and these differences offer clues about optimizing treatment strategies.