Overexpression of bacteriophage T4 and T7 endolysins differentially regulate the metabolic fingerprint of host Escherichia coli

Kairamkonda, Manikyaprabhu; Sharma, Meenakshi; Gupta, Payal; Poluri, Krishna Mohan

doi:10.1016/j.ijbiomac.2022.09.012

Cited by 4 publications

(3 citation statements)

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“…Metabolite(s) concentration data set was preprocessed using interquartile range data filtering, sample normalization using median, accompanied with square root transformation, followed by pareto scaling. − The normalized data set was analyzed using the univariate and multivariate statistical analyses in order to highlight the metabolic differences between the Rb patients and controls. Univariate analysis was performed using the Log2 fold change and t test to identify the statistically significant metabolites exhibiting the relative fold change (FC ≥ 1.4) in their concentrations among the two groups. , …”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…Univariate analysis was performed using the Log2 fold change and t test to identify the statistically significant metabolites exhibiting the relative fold change (FC ≥ 1.4) in their concentrations among the two groups. 124,125 Multivariate statistical analysis, which includes principal component analysis (PCA), and partial least-squares discriminant analysis (PLS-DA) were conducted to identify the imperative metabolites contributing to the discrimination of the two groups. PCA is an unsupervised statistical analysis method which was used to obtain an overall grouping trend and to decode the outliers on the basis of variance across the data set.…”

Section: Nmr Data Processing and Metabolitementioning

confidence: 99%

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Serum Metabolomics of Retinoblastoma: Assessing the Differential Serum Metabolic Signatures of Unilateral and Bilateral Patients

Gulati,

Manukonda,

Kairamkonda

et al. 2023

ACS Omega

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Retinoblastoma (Rb) is the most common pediatric eye cancer. To identify the biomarkers for early diagnosis and monitoring the progression of Rb in patients, mapping of the alterations in their metabolic profiles is essential. The present study aims at exploring the metabolic disparity in serum from Rb patients and controls using NMR-based metabolomics. A total of 72 metabolites, including carbohydrates, amino acids, and organic acids, were quantified in serum samples from 24 Rb patients and 26 controls. Distinct clusters of Rb patients and controls were obtained using the partial least-squares discriminant analysis (PLS-DA) model. Further, univariate and multivariate analyses of unilateral and bilateral Rb patients with respect to their age-matched controls depicted their distinct metabolic fingerprints. Metabolites including 2-phosphoglycerate, 4-aminobutyrate, proline, O -phosphocholine, O -phosphoethanolamine, and Sn-glycero-3-phosphocholine (Sn-GPC) showed significant perturbation in both unilateral and bilateral Rb patients. However, metabolic differences among the bilateral Rb cases were more pronounced than those in unilateral Rb cases with respect to controls. In addition to major discriminatory metabolites for Rb, unilateral and bilateral Rb cases showed specific metabolic changes, which might be the result of their differential genetic/somatic mutational backgrounds. This further suggests that the aberrant metabolic perturbation in bilateral patients signifies the severity of the disease in Rb patients. The present study demonstrated that identified serum metabolites have potential to serve as a noninvasive method for detection of Rb, discriminate bilateral from unilateral Rb patients, and aid in better understanding of the RB tumor biology.

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